Methods and device for determining a valid intrinsic frequency

ABSTRACT

Described are methods and a device for determining a valid intrinsic alpha frequency. Described herein are methods and a device for determining the appropriate intrinsic alpha frequency (IAF) to be applied for neuro-EEG synchronization therapy using alternating magnetic fields to gently “tune” the brain and affect the mood, focus and cognition of subjects. Methods and a device described herein use an algorithm to quantitatively analyze EEG recordings to determine if recorded EEG frequencies are valid, and if necessary, requiring additional recordings and analysis until a valid EEG is found. Methods and devices described herein can be utilized to calculate the intrinsic frequency of other EEG bands, including the Theta, Beta Gamma and Delta bands.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a non-provisional of, and claims the benefitof, U.S. Provisional Application No. 62/038,148 filed on Aug. 15, 2014,the entire contents of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

Mental disorders generate serious problems for the affected people,their families, and society. Currently, psychiatrists andneurophysiologists treat these disorders with a variety of medications,many of which have significant negative side effects.

Repetitive Transcranial Magnetic Stimulation (rTMS) uses anelectromagnet placed on the scalp that generates a series of magneticfield pulses roughly the strength of an MRI scan. Some studies haveshown that rTMS can reduce the negative symptoms of schizophrenia,depression and other mental disorders under certain circumstances. TheNEST (Neuro-EEG Synchronization Therapy) is specifically tailored todeliver low amplitude stimulation at the patient's intrinsic alphafrequency (IAF). Therefore it is imperative that a stable, repeatableIAF value be obtained.

SUMMARY OF THE INVENTION

Described herein are methods and devices for utilizing an algorithm bywhich a valid intrinsic alpha frequency (IAF) is determined byquantitatively analyzing EEG recordings one at a time to determinewhether or not they are valid, and requiring additional recordings untila valid IAF is found, or until the algorithm determines that a valid IAFcannot be found.

Provided herein is a method of determining a final intrinsic alphafrequency of a subject comprising: applying an EEG discriminationroutine comprising: obtaining a first EEG recording in a time domain;dividing the first EEG recording into a plurality of epochs, eachcomprising a segment of data, wherein a total number of epochs is N;filtering the segment of data of each epoch using a high-pass filter;converting each epoch into a frequency domain epoch (i); filtering eachfrequency domain epoch (i) using a smoothing filter; calculating anepoch intrinsic alpha frequency (m_(i)) of each frequency domain epoch(i); calculating a mean (M) intrinsic alpha frequency (IAF) of allintrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,if |m_(I)−M|>0.5 Hz, removing the farthest frequency domain epoch(m_(I)), decrementing N, and returning to step g), or if |m_(I)−M|≤0.5Hz, continuing to next step; setting a final intrinsic alpha frequency(fIAF) equal to M; and outputting the final intrinsic alpha frequency(fIAF) to a user or to a device.

In some embodiments, wherein determining a farthest frequency domainepoch (m_(I)) from the mean M comprises calculating an index (I) of thefrequency domain epoch that is farthest from the mean (M), whereinI=Index(max_(i)|m_(i)−M|).

In some embodiments, the first EEG recording length is 128 seconds. Insome embodiments, the first EEG recording is a single-channel recording.In some embodiments, the first EEG recording is a multi-channelrecording, wherein an IAF estimate is made for each channel in an epochand averaged together, or wherein each channel is treated separately,generating an IAF estimate for each channel for the full EEG recording,and wherein valid IAF estimates from each channel, as determined by thestep; determining a farthest frequency domain epoch (m_(I)) from themean M, if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)), decrementing N, and returning to step g), or if|m_(I)−M≤0.5 Hz, are averaged together to generate a final IAF. In someembodiments, a channel of the first EEG recording initially comprises 16epochs. In some embodiments, the epoch intrinsic alpha frequency (m_(i))of each frequency domain epoch (i) is calculated from 7.0 Hz to 14.0 Hz.In some embodiments, the final intrinsic alpha frequency (fIAF) is from8.0 Hz to 13.0 Hz. In some embodiments, the first EEG recordingcomprises a sample rate of 128 samples/sec. In some embodiments, thehigh-pass filter comprises a 4^(th) order Butterworth IIR filter withthe 3 dB cutoff set to 5.0 Hz. In some embodiments, the epoch intrinsicalpha frequency of each epoch (m_(i)) is determined using a Fast FourierTransform (FFT). In some embodiments, the Fast Fourier Transform (FFT)uses a resolution of 1024 points, which results in a 0.125 Hz resolutionper bin from 0 Hz to 64 Hz. In some embodiments, the Fast FourierTransform (FFT) is smoothed with an averaging filter that averages the 5points±2 from the target. In some embodiments, if a standard deviation(SD) of the N epoch IAF values ≥0.75 Hz, a second EEG recording isobtained and the previously described method of determining a finalintrinsic alpha frequency of a subject (using a first EEG recording) isrepeated using the second EEG recording in place of the first EEGrecording. In some embodiments, if a second standard deviation (SD) ofthe N epoch IAF values ≥0.75 Hz obtained using the second EEG recording,a third EEG recording is obtained and the previously described method ofdetermining a final intrinsic alpha frequency of a subject (using afirst EEG recording) is repeated using the third EEG recording in placeof the first EEG recording. In some embodiments, if a third standarddeviation (SD) of the N epoch IAF values ≥0.75 Hz obtained using thethird EEG recording, a range of fIAF intrinsic alpha frequencies (fIAFs)of the first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic alpha frequencies (fIAFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic alpha frequency (vIAF). In stillother embodiments, if the final intrinsic alpha frequency (fIAF) is <8.0Hz or >13.0 Hz, a second EEG recording is obtained and the previouslydescribed method of determining a final intrinsic alpha frequency of asubject (using a first EEG recording) is repeated using the second EEGrecording in place of the first EEG recording. In still otherembodiments, if the final intrinsic alpha frequency (fIAF) calculatedusing the second EEG recording is <8.0 Hz or >13.0 Hz, a third EEGrecording is obtained and the previously described method of determininga final intrinsic alpha frequency of a subject (using a first EEGrecording) is repeated using the third EEG recording in place of thefirst EEG recording. In still other embodiments, if the final intrinsicalpha frequency (fIAF) calculated using the third EEG recording is <8.0Hz or >13.0 Hz, a range of fIAF intrinsic alpha frequencies (fIAFs) ofthe first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic alpha frequencies (fIAFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic alpha frequency (vIAF). Stillfurther, in other embodiments, if the final intrinsic alpha frequency(fIAF) of the EEG is from 8.0 Hz-13.0 Hz and the standard deviation (SD)of the N epoch IAF values is <0.75 Hz, the final intrinsic alphafrequency (fIAF) is determined to be a valid intrinsic alpha frequency(vIAF).

In some embodiments of the method of determining a final intrinsic alphafrequency of a subject; if a standard deviation (SD) of the N epoch IAFvalues ≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) is<8.0 Hz or >13.0 Hz, then a second EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe second EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the second EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the second EEG readingis <8.0 Hz or >13.0 Hz, then a third EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe third EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the third EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the third EEG readingis <8.0 Hz or >13.0 Hz, then a fourth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe fourth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the fourth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the fourth EEG readingis <8.0 Hz or >13.0 Hz, then a fifth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe fifth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the fifth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the fifth EEG readingis <8.0 Hz or >13.0 Hz, then a sixth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe sixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the sixth EEG readingis <8.0 Hz or >13.0 Hz, then a seventh EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe seventh EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the seventh EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the seventh EEGreading is <8.0 Hz or >13.0 Hz, then a eighth EEG recording is obtainedand the previously described method of determining a final intrinsicalpha frequency of a subject (using a first EEG recording) is repeatedusing the eighth EEG recording in place of the first EEG recording. Insome embodiments, if the final intrinsic alpha frequency (fIAF)calculated using the third EEG recording is <8.0 Hz or >13.0 Hz or ifthe standard deviation (SD) of the N epoch IAF values calculated usingthe third EEG reading ≥0.75 Hz, a range of fIAF intrinsic alphafrequencies (fIAFs) of the first EEG recording, the second EEG recordingand the third EEG recording is calculated, wherein if the range is <2.0Hz, then the mean value of the final intrinsic alpha frequencies (fIAFs)of the first EEG recording, the second EEG recording and the third EEGrecording is determined to be the Valid intrinsic alpha frequency(vIAF). In still other embodiments, if the final intrinsic alphafrequency (fIAF) calculated using the eighth EEG recording is <8.0 Hzor >13.0 Hz or if the standard deviation (SD) of the N epoch IAF valuescalculated using the eighth EEG reading ≥0.75 Hz, a range of fIAFintrinsic alpha frequencies (fIAFs) of the at least three of the firstEEG recording, the second EEG recording, the third EEG recording, thefourth EEG recording, the fifth EEG recording, the sixth EEG recording,the seventh EEG recording, the eighth EEG recording is calculated,wherein if the range is <2.0 Hz, then the mean value of the finalintrinsic alpha frequencies (fIAFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, the eighth EEG recording is determined to be theValid intrinsic alpha frequency (vIAF).

Provided herein is a method of determining a final intrinsic alphafrequency of a subject comprising applying an EEG discrimination routinecomprising: obtaining a multi-channel EEG recording in a time domain;dividing the multi-channel EEG recording into a plurality of epochs,each epoch comprising a corresponding data segment from each channel,and averaging the data segments in each epoch together, wherein a totalnumber of epochs is N; filtering the data segments of each epoch using ahigh-pass filter; converting each epoch into a frequency domain epoch(i); filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic alpha frequency (m_(i)) of each frequencydomain epoch (i); calculating a mean (M) intrinsic alpha frequency (IAF)of all intrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,wherein, i) if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)), decrementing N, and returning to step g), or, ii) if|m_(I)−M|≤0.5 Hz, continuing to next step; setting a final intrinsicalpha frequency (fIAF) equal to M; and outputting the final intrinsicalpha frequency (fIAF) to a user or to a device.

In some embodiments, a channel intrinsic alpha frequency (cIAF) isdetermined for each channel in the frequency domain epoch (i) of amulti-channel EEG recording, and they are averaged together to generatethe epoch intrinsic alpha frequency (m_(i)). In some embodiments, theepoch intrinsic alpha frequency (m_(i)) is generated by averagingchannel intrinsic alpha frequencies generated from the channels meetinginclusion criteria and averaged together, wherein the inclusion criteriacomprise: i) a greatest alpha power as compared to all other channels ofthe EEG recording; ii) a lowest variance as compared to all otherchannels of the EEG recording; or iii) a highest Q-factor as compared toall other channels of the EEG recording.

In some embodiments, an epoch intrinsic alpha frequency (m_(i)) isgenerated by averaging channel intrinsic alpha frequencies generatedfrom the channels meeting inclusion criteria and averaged together,wherein the inclusion criteria comprise: a greatest alpha power ascompared to all other channels of the EEG recording; a lowest varianceas compared to all other channels of the EEG recording; or a highestQ-factor as compared to all other channels of the EEG recording.

In some embodiments, a multiple-channel time domain EEG recording may beused, wherein different options exist for determining the intrinsicalpha frequency (IAF). In one embodiment, each channel from the firstmulti-channel time domain EEG recording is treated separately andgenerates a channel intrinsic alpha frequency (cIAF) for each channel ofthe full time domain EEG recording, wherein a number of channelintrinsic alpha frequencies (cIAFs) is equal to the number of channelsfrom the first multi-channel time domain EEG recording. In someembodiments, all channel intrinsic alpha frequencies (cIAFs) from thefirst multi-channel time domain EEG recording are averaged together toobtain a representative intrinsic alpha frequency (IAF) of themulti-channel time domain EEG recording. In some embodiments the channelintrinsic alpha frequency (cIAF) of a single channel of the firstmulti-channel time domain EEG recording is within a band between 8.0Hz-13.0 Hz; has a standard deviation (SD) below 0.75 Hz; has the lowest(SD) of all the channel intrinsic alpha frequencies (cIAFs) of themulti-channel time domain EEG recording; and is selected as arepresentative intrinsic alpha frequency (IAF) of the multi-channel timedomain EEG recording. Still further, all channel intrinsic alphafrequencies (cIAFs) of channels of the first multi-channel time domainEEG recording that are within a band between 8.0 Hz-13.0 Hz; and have astandard deviation (SD) below 0.75 Hz; are averaged together to obtain arepresentative intrinsic alpha frequency (IAF) of the multi-channel timedomain EEG recording.

Provided herein is a method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject comprising: applying an EEGdiscrimination routine comprising: obtaining a first EEG recording in atime domain; dividing the first EEG recording into a plurality ofepochs, wherein a total number of epochs is N; filtering the data usinga high-pass filter (to reduce the influence of heartbeat and lowfrequency noise); converting each epoch into a frequency domain epoch(i); filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic frequency (m_(i)) in an EEG band of eachfrequency domain epoch (i); calculating a mean (M) intrinsic frequency(IF) in the EEG band of all epoch intrinsic frequencies (m_(i-N)),wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining the farthest frequency domain epoch (m_(I)) from the mean,wherein if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)) decrementing N, and returning to the step for calculatinga mean (M) intrinsic frequency (IF) in the band of all epoch intrinsicfrequencies, or if |m_(I)−M|≤0.5 Hz, then; continue to the next step forsetting a final intrinsic frequency (fIF) equal to M; and outputting thefinal intrinsic frequency (fIF) in the EEG band equal to M; andoutputting the final intrinsic frequency (fIF) in the EEG band to a useror device. In some embodiments, wherein determining a farthest frequencydomain epoch (m_(I)) from the mean M comprises determining an index (I)of the frequency domain epoch that is farthest from the mean (M),wherein I=Index(max_(i)|m_(i)−M|). In some embodiments, the EEG bandcomprises: an Alpha band; a Theta band; a Beta band; a Gamma band; and aDelta band. In some embodiments, the EEG recording length is 128seconds. In some embodiments, the EEG recording is a single-channelrecording. In some embodiments, the EEG recording is a multi-channelrecording. In some embodiments the EEG is a multi-channel recording,wherein a channel intrinsic frequency (cIF) estimate may be made foreach channel in an epoch and averaged together, or wherein each channelis treated separately, generating a final intrinsic frequency (fIF)estimate for each channel for the full EEG recording, and wherein finalintrinsic frequency estimates from each channel, as determined by steph), are averaged together to generate a final intrinsic frequency (fIF).In some embodiments, a channel of the EEG comprises 16 epochs. In someembodiments, the calculated epoch intrinsic frequency (m_(i)) of the EEGcomprises a range that is at least: ±0.5 Hz outside the range of the EEGband; ±1.0 Hz outside the range of the EEG band; ±1.5 Hz outside therange of the EEG band; and ±2.0 Hz outside the range of the EEG band. Insome embodiments, the EEG recording comprises a sample rate of 128samples/sec. In some embodiments, the high-pass filter uses a 4^(th)order Butterworth IIR filter with the 3 dB cutoff set to 5.0 Hz. In someembodiments, the epoch intrinsic frequency of each epoch (m_(i)) isdetermined using a Fast Fourier Transform (FFT). In some embodiments,the Fast Fourier Transform (FFT) uses a resolution of 1024 points, whichresults in a 0.125 Hz resolution per bin from 0 Hz to 64 Hz. In someembodiments, the Fast Fourier Transform (FFT) is smoothed with anaveraging filter that averages 5 points±2 from the target. In someembodiments, if the standard deviation (SD) of the N epoch IF value is≥0.75 Hz, a second EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe second EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the second EEG recording is ≥0.75 Hz, a third EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the third EEG recording in placeof the first recording. In some embodiments, if the standard deviation(SD) of the N epoch IF values calculated using the third EEG recordingis ≥0.75 Hz, a fourth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe fourth EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the fourth EEG recording is ≥0.75 Hz, a fifth EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the fifth EEG recording in placeof the first recording. In some embodiments, if the standard deviation(SD) of the N epoch IF values calculated using the fifth EEG recordingis ≥0.75 Hz, a sixth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe sixth EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG recording is ≥0.75 Hz, a seventh EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the seventh EEG recording inplace of the first recording. In some embodiments, if the standarddeviation (SD) of the N epoch IF values calculated using the seventh EEGrecording is ≥0.75 Hz, an eighth EEG recording is obtained and thepreviously described method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject (using a first EEG recording) isrepeated using the eighth EEG recording in place of the first recording.In still other embodiments, if the eighth standard deviation (SD) of theN epoch IF values is ≥0.75 Hz obtained using the eighth EEG recording, arange of final intrinsic frequencies (fIFs) of at least three of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, and the eighth EEG recording iscalculated, wherein if the range is <2.0 Hz, then the mean value of thefinal intrinsic frequencies (fIFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is determined to bethe Valid intrinsic frequency (vIF). In some embodiments, if a thirdstandard deviation (SD) of the N epoch IF values ≥0.75 Hz obtained usingthe third EEG recording, a range of final intrinsic frequencies (fIFs)of the first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic frequencies (fIFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic frequency (vIF). In someembodiments of the method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject, if the final intrinsic frequency(fIF) of the EEG recording is > a predetermined amount outside the EEGband, a second EEG recording is obtained and the method of determining avalid intrinsic frequency (vIF) of an EEG band of a subject is repeatedusing the second EEG recording in place of the first EEG recording. Insome embodiments, the predetermined amount is: ±0.5 Hz; ±1.0 Hz; ±1.5Hz; or ±2.0 Hz. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the second EEG recording is >the predetermined amount outside the EEG band, a third EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the third EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the third EEG recording is >the predetermined amount outside the EEG band, a fourth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the fourth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the fourth EEG recording is >the predetermined amount outside the EEG band, a fifth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the fifth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the fifth EEG recording is >the predetermined amount outside the EEG band, a sixth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the sixth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the sixth EEG recording is >the predetermined amount outside the EEG band, a seventh EEG recordingis obtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the seventh EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the seventh EEG recording is >the predetermined amount outside the EEG band, an eighth EEG recordingis obtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the eighth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) calculated using the third EEG recording is > the predeterminedamount outside the EEG band, a range of final intrinsic frequencies(fIFs) of the first EEG recording, the second EEG recording and thethird EEG recording is calculated, wherein if the range is <2.0 Hz, thenthe mean value of the final intrinsic frequencies (fIFs) of the firstEEG recording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic frequency (vIF). In someembodiments, if the final intrinsic frequency (fIF) calculated using thethird EEG recording is > the predetermined amount outside the EEG band,a range of final intrinsic frequencies (fIFs) of three or more of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, and the eighth EEG recording iscalculated, wherein if the range is <2.0 Hz, then the mean value of thefinal intrinsic frequencies (fIFs) of the three or more of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is determined to bethe Valid intrinsic frequency (vIF).

In some embodiments of the method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject, if a standard deviation(SD) of the N epoch IF values ≥0.75 Hz, or if the final intrinsicfrequency (fIF) is > a predetermined amount outside the EEG band,wherein the predetermined amount is ±0.5 Hz, ±1.0 Hz, ±1.5 Hz, or ±2.0Hz; then a second EEG recording is obtained and the previously describedmethod of determining a valid intrinsic frequency (vIF) of an EEG bandof a subject (using a first EEG recording) is repeated using the secondEEG recording in place of the first EEG recording. In some embodiments,if a standard deviation (SD) of the N epoch IF values calculated usingthe second EEG reading ≥0.75 Hz, or if the final intrinsic frequency(fIF) calculated using the second EEG reading is > the predeterminedamount outside the EEG band, then a third EEG recording is obtained andthe previously described method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the third EEG recording in place of thefirst EEG recording. In some embodiments, if a standard deviation (SD)of the N epoch IF values calculated using the third EEG reading ≥0.75Hz, or if the final intrinsic frequency (fIF) calculated using the thirdEEG reading is > the predetermined amount outside the EEG band, then afourth EEG recording is obtained and the previously described method ofdetermining a valid intrinsic frequency (vIF) of an EEG band of asubject (using a first EEG recording) is repeated using the fourth EEGrecording in place of the first EEG recording. In some embodiments, if astandard deviation (SD) of the N epoch IF values calculated using thefourth EEG reading ≥0.75 Hz, or if the final intrinsic frequency (fIF)calculated using the fourth EEG reading is > the predetermined amountoutside the EEG band, then a fifth EEG recording is obtained and thepreviously described method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject (using a first EEG recording) isrepeated using the fifth EEG recording in place of the first EEGrecording. In some embodiments, if a standard deviation (SD) of the Nepoch IF values calculated using the fifth EEG reading ≥0.75 Hz, or ifthe final intrinsic frequency (fIF) calculated using the fifth EEGreading is > the predetermined amount outside the EEG band, then a sixthEEG recording is obtained and the method of claim 35 is repeated usingthe sixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the sixth EEG reading is >the predetermined amount outside the EEG band, then a seventh EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the seventh EEG recording inplace of the first EEG recording. In some embodiments, if a standarddeviation (SD) of the N epoch IF values calculated using the seventh EEGreading ≥0.75 Hz, or if the final intrinsic frequency (fIF) calculatedusing the seventh EEG reading is > the predetermined amount outside theEEG band, then a eighth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe eighth EEG recording in place of the first EEG recording. In stillfurther embodiments, if the final intrinsic frequency (fIF) calculatedusing the third EEG recording is > the predetermined amount outside theEEG band, or if the standard deviation (SD) of the N epoch IF valuescalculated using the third EEG reading ≥0.75 Hz, a range of finalintrinsic frequencies (fIFs) of the first EEG recording, the second EEGrecording and the third EEG recording is calculated, wherein if therange is <2.0 Hz, then the mean value of the final intrinsic frequencies(fIFs) of the first EEG recording, the second EEG recording and thethird EEG recording is determined to be the Valid intrinsic frequency(vIF). Further still, in some embodiments, if the final intrinsicfrequency (fIF) calculated using the eighth EEG recording is > thepredetermined amount outside the EEG band or if the standard deviation(SD) of the N epoch IF values calculated using the eighth EEG reading≥0.75 Hz, a range of final intrinsic frequencies (fIFs) of the at leastthree of the first EEG recording, the second EEG recording, the thirdEEG recording, the fourth EEG recording, the fifth EEG recording, thesixth EEG recording, the seventh EEG recording, the eighth EEG recordingis calculated, wherein if the range is <2.0 Hz, then the mean value ofthe final intrinsic frequencies (fIFs) of the at least three of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, the eighth EEG recording isdetermined to be the Valid intrinsic frequency (vIF).

In some embodiments of the method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject, if the final intrinsicfrequency (fIF) is within the EEG band and the standard deviation (SD)of the N epoch IF value is <0.75 Hz, the final intrinsic frequency (fIF)is determined to be a valid intrinsic frequency (vIF). In someembodiments, a channel intrinsic frequency (cIF) is determined for eachchannel in the frequency domain epoch (i), and they are averaged togenerate the epoch intrinsic frequency (m_(i)). In some embodiments, anepoch intrinsic frequency (m_(i)) is generated by averaging channelintrinsic frequencies (cIFs) generated from the channels meetinginclusion criteria and averaged together, wherein the inclusion criteriacomprise: a greatest power in the EEG band as compared to all otherchannels of the EEG recording; a lowest variance as compared to allother channels of the EEG recording; or a highest Q-factor as comparedto all other channels of the EEG recording.

Further still, in some embodiments, each channel from a multi-channeltime domain EEG recording is treated separately and generates a channelintrinsic frequency (cIF) for each channel of the full time domain EEGrecording, wherein a number of channel intrinsic frequencies (cIFs) isequal to the number of channels. In other embodiments, all channelintrinsic frequencies (cIFs) from a multi-channel time domain EEGrecording are averaged together to obtain a representative intrinsicfrequency (IF) of the time domain EEG recording. In some embodiments, asingle channel intrinsic frequency (cIF) of a multi-channel time domainEEG recording comprises: a standard deviation (SD) below 0.75 Hz; thelowest (SD) of all the channel intrinsic frequencies (cIFs) of themulti-channel time domain EEG recording; and is selected as arepresentative intrinsic frequency (IF) for the time domain EEGrecording. In still other embodiments, the channel intrinsic frequencies(cIFs) of all channels of a multi-channel time domain EEG recording thathave a standard deviation (SD) below 0.75 Hz; are averaged together toobtain a representative intrinsic frequency (IF) of the multi-channeltime domain EEG recording.

Provided herein is a device comprising a computer-implemented systemconfigured to discriminate a valid intrinsic alpha frequency of at leastone time domain EEG recording of a subject comprising a software modulewith a routine configured to: evaluate a first time domain EEG recordingof a subject; determine if the time domain EEG recording has a stableintrinsic alpha frequency (m_(i)) throughout a plurality of epochswherein a valid intrinsic alpha frequency comprises; a standarddeviation between the epochs is <0.75 Hz, and a mean (M) of epochintrinsic alpha frequencies (m_(i)) between 8.0 Hz to 13.0 Hz; set afinal intrinsic alpha frequency (fIAF) equal to M; and output the finalintrinsic alpha frequency (fIAF) to the device; or, label the first timedomain EEG recording suspect; and continue to sequentially evaluate aplurality of subsequent time domain EEG recordings until a validintrinsic alpha frequency can be obtained from a subsequent time domainEEG recording. In some embodiments of the computer implemented system, atotal number of time domain EEG recordings is eight. In some embodimentsof the computer implemented system, if the software module routinecannot obtain a valid intrinsic alpha frequency within the first timedomain EEG recording, a second time domain EEG recording or a third timedomain EEG recording, a range of epoch intrinsic alpha frequencies(m_(i)) of the first time domain EEG recording, the second time domainEEG recording and the third time domain EEG recording is calculated,wherein if the range is <2.0 Hz, the mean (M) of the first time domainEEG recording, the second time domain EEG recording and the third timedomain EEG recording is calculated and is set equal to the finalintrinsic alpha frequency (fIAF). In some embodiments of the computerimplemented system, if the software module routine cannot obtain a validintrinsic alpha frequency within eight time domain EEG recordings, thesoftware module routine ends and outputs a message to a user that avalid intrinsic alpha frequency cannot be found. In some embodiments,the device comprises a Neuro-EEG Synchronization Therapy (NEST) device.In some embodiments, the device is configured to deliver low amplitudestimulation at an intrinsic alpha frequency that is the same as apatient's intrinsic alpha frequency.

Provided herein is a method of quantitatively analyzing EEG recordingsto obtain a valid Intrinsic Alpha Frequency of a subject using aNeuro-EEG Synchronization Therapy (NEST) device comprising: obtaining asingle 128-second time domain EEG recording; dividing the 128-second EEGrecording into sixteen eight-second epochs; converting each epoch into afrequency domain epoch (i); calculating an epoch intrinsic alphafrequency (m_(i)) for each frequency domain epoch (i); successivelyeliminating the epoch intrinsic alpha frequencies (m_(i)) that arefarthest from a mean, until the remaining epoch intrinsic alphafrequencies (m_(i)) are all within 0.5 Hz of the mean; and outputting afinal intrinsic alpha frequency (fIAF) for the EEG recording that isequal to the mean value of the remaining epochs' epoch intrinsic alphafrequencies. In some embodiments, the final intrinsic alpha frequency(fIAF) is determined to be valid if the standard deviation of the epochintrinsic alpha frequencies (m_(i)) from the epochs is <0.75 Hz and thefinal intrinsic alpha frequency (fIAF) is within the band of 8.0-13.0Hz. In some embodiments, the final intrinsic alpha frequency (fIAF) isdetermined to be suspect if a standard deviation of the epoch intrinsicalpha frequencies (m_(i)) from the epochs is ≥0.75 Hz or the finalintrinsic alpha frequency (fIAF) is outside the band of 8.0-13.0 Hz, andwherein a second EEG is recorded is obtained to determine if a validintrinsic alpha frequency (vIAF) can be determined as definedpreviously, by replacing the single 128-second time domain EEG recordingwith the second EEG recording. In some embodiments, the final intrinsicalpha frequency (fIAF) using the second EEG recording is determined tobe suspect if a standard deviation of the epoch intrinsic alphafrequencies (m_(i)) from the epochs is ≥0.75 Hz or the final intrinsicalpha frequency (fIAF) is outside the band of 8.0-13.0 Hz, and wherein athird EEG recording is obtained to determine if the valid intrinsicalpha frequency (vIAF) can be determined as defined previously, byreplacing the single 128-second time domain EEG recording with the thirdEEG recording. In some embodiments, if the valid intrinsic alphafrequency (vIAF) cannot be obtained using the third EEG recording, arange of the final intrinsic alpha frequency (fIAF) values of the threeprevious EEG recordings is calculated, and if the range of the previousthree final intrinsic alpha frequency (fIAF) values is <2.0 Hz, then thevalid Intrinsic Alpha Frequency (vIAF) is set to the mean of the threeprevious final Intrinsic Alpha Frequencies (fIAFs).

In some embodiments of the method of determining a final intrinsic alphafrequency of a subject, wherein determining the farthest frequencydomain epoch (m_(I)) from the mean M comprises calculating an index (I)of the frequency domain epoch that is farthest from the mean (M),wherein I=Index(max_(i)|m_(i)−M|). In some embodiments of the method ofdetermining a valid intrinsic frequency of an EEG band of a subject,wherein determining the farthest frequency domain epoch (m_(i)) from themean M comprises calculating an index (I) of the frequency domain epochthat is farthest from the mean (M), wherein I=Index(max_(i)|m_(i)−M|).

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention will be obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIG. 1 is an illustrative flowchart of one aspect of the EEGDiscrimination Algorithm

FIG. 2 is an illustrative flowchart of one aspect of theInclusion/Exclusion decision tree for evaluation of the validity of theIAF.

FIG. 3 is an illustrative example of a 128 second EEG recording dividedinto 16 Epochs.

FIG. 4 is an illustrative example of a single epoch plot, showing thefiltered EEG (top plot), along with the FFT of the epoch (bottom plot),focusing on the frequency between 0-20 Hz. The window size of 7-14 Hz isshown by 2 vertical lines.

FIG. 5 is an illustrative example of raw EEG waveforms (top panel ofimage per phase) and FFT waveforms for the raw EEG waveform (bottompanel of image per phase).

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a novel method in which a subject's EEGis evaluated to either find a valid intrinsic alpha frequency (vIAF) orto require an additional recording. A subject's EEG is quantitativelyanalyzed with an algorithm by reviewing discreet epochs of an EEG,analyzing epoch IAFs of each epoch (m_(i)), successively pruning thevalues of these epoch IAFs until the remaining epoch-IAFs values arewithin a specific range of the mean. The final IAF estimate for that EEGis equal to the mean value of the remaining epochs' IAFs. This final IAF(fIAF) is utilized as a primary setting for Neuro-EEG SynchronizationTherapy (NEST) Using Low Frequency Magnetic Stimulation with a NESTdevice. The NEST device is specifically tailored to deliver lowamplitude stimulation at the patient's intrinsic alpha frequency (IAF).

The present invention describes an EEG algorithm to determine a validIAF (vIAF). It is different, but, in part, derived from the IAFalgorithm from U.S. Pat. No. 8,585,568—SYSTEMS AND METHODS FORNEURO-EEG-SYNCHRONIZATION THERAPY.

A recent published paper by Leuchter, et al. (2013) states that aneffect on the symptoms of Major Depressive Disorder (MDD) will beobtained when the treatment frequency is delivered at the subject's IAF.In addition, a paper by Arns, et al. (2010) shows that using an rTMSpulse rate 1.0 Hz away from the subject's IAF does not result insignificant benefit to the patient.

Therefore, it is imperative that a stable, repeatable IAF value beobtained. Thus in a clinical trial setting, subjects having an EEG ofsufficient duration and quality that can be processed for quantitativeanalysis should be of primary interest for inclusion, and that a validIAF can be obtained for each patient.

Described herein are methods and devices for utilizing an algorithm bywhich a valid intrinsic alpha frequency (vIAF) is determined byquantitatively analyzing EEG recordings one at a time to determinewhether or not they are valid, and if necessary, requiring additionalrecordings until a valid EEG is found.

Provided herein is a method of determining a final intrinsic alphafrequency of a subject comprising: applying an EEG discriminationroutine comprising: obtaining a first EEG recording in a time domain;dividing the first EEG recording into a plurality of epochs, eachcomprising a segment of data, wherein a total number of epochs is N;filtering the segment of data of each epoch using a high-pass filter;converting each epoch into a frequency domain epoch (i); filtering eachfrequency domain epoch (i) using a smoothing filter; calculating anepoch intrinsic alpha frequency (m_(i)) of each frequency domain epoch(i); calculating a mean (M) intrinsic alpha frequency (IAF) of allintrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,if |m_(I)−M|>0.5 Hz, removing the farthest frequency domain epoch(m_(I)), decrementing N, and returning to step g), or if |m_(I)−M|≤0.5Hz, continuing to next step; setting a final intrinsic alpha frequency(fIAF) equal to M; and outputting the final intrinsic alpha frequency(fIAF) to a user or to a device.

Disclosed herein, in various embodiments, are methods of determining afinal intrinsic alpha frequency of a subject in a neuro-EEGsynchronization therapy comprising: applying an EEG discriminationroutine comprising: receiving a first EEG recording obtained from an EEGsensor in a time domain; segmenting the first EEG recording into aplurality of epochs, each comprising a segment of data, wherein a totalnumber of epochs is N; filtering the segment of data of each epoch usinga high-pass filter; converting each epoch into a frequency domain epoch(i); filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic alpha frequency (m_(i)) of each frequencydomain epoch (i); calculating a mean (M) intrinsic alpha frequency (IAF)of all intrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,if |m_(I)−M|>0.5 Hz, removing the farthest frequency domain epoch(m_(I)), decrementing N, and returning to step g), or if |m_(I)−M|≤0.5Hz, continuing to next step; setting a final intrinsic alpha frequency(fIAF) equal to M; and outputting the final intrinsic alpha frequency(fIAF) to a user or to a neuro-EEG synchronization therapy device;utilizing the final intrinsic alpha frequency (fIAF) in the neuro-EEGsynchronization therapy. In some embodiments, the first EEG recordinglength is 128 seconds. In some embodiments, the first EEG recording is asingle-channel recording. In some embodiments, the first EEG recordingis a multi-channel recording, wherein an IAF estimate is made for eachchannel in an epoch and averaged together, or wherein each channel istreated separately, generating an IAF estimate for each channel for thefull EEG recording, and wherein valid IAF estimates from each channel,as determined by step h), are averaged together to generate a final IAF.In some embodiments, a channel of the first EEG recording initiallycomprises 16 epochs. In some embodiments, the epoch intrinsic alphafrequency (m_(i)) of each frequency domain epoch (i) is calculated from7.0 Hz to 14.0 Hz. In some embodiments, the final intrinsic alphafrequency (fIAF) is from 8.0 Hz to 13.0 Hz. In some embodiments, thefirst EEG recording comprises a sample rate of 128 samples/sec. In someembodiments, the high-pass filter comprises a 4^(th) order ButterworthIIR filter with the 3 dB cutoff set to 5.0 Hz. In some embodiments, theepoch intrinsic alpha frequency of each epoch (m_(i)) is determinedusing a Fast Fourier Transform (FFT). In some embodiments, the FastFourier Transform (FFT) uses a resolution of 1024 points, which resultsin a 0.125 Hz resolution per bin from 0 Hz to 64 Hz. In someembodiments, the Fast Fourier Transform (FFT) is smoothed with anaveraging filter that averages the 5 points±2 from the target. In someembodiments, if a standard deviation (SD) of the N epoch IAF values≥0.75 Hz, a second EEG recording is obtained and the method of claim 1is repeated using the second EEG recording in place of the first EEGrecording. In some embodiments, if a second standard deviation (SD) ofthe N epoch IAF values ≥0.75 Hz obtained using the second EEG recording,a third EEG recording is obtained and the method of claim 1 is repeatedusing the third EEG recording in place of the first EEG recording. Insome embodiments, if a third standard deviation (SD) of the N epoch IAFvalues ≥0.75 Hz obtained using the third EEG recording, a range of fIAFintrinsic alpha frequencies (fIAFs) of the first EEG recording, thesecond EEG recording and the third EEG recording is calculated, whereinif the range is <2.0 Hz, then the mean value of the final intrinsicalpha frequencies (fIAFs) of the first EEG recording, the second EEGrecording and the third EEG recording is determined to be the Validintrinsic alpha frequency (vIAF). In some embodiments, if the finalintrinsic alpha frequency (fIAF) is <8.0 Hz or >13.0 Hz, a second EEGrecording is obtained and the method of claim 1 is repeated using thesecond EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic alpha frequency (fIAF) calculatedusing the second EEG recording is <8.0 Hz or >13.0 Hz, a third EEGrecording is obtained and the method of claim 1 is repeated using thethird EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic alpha frequency (fIAF) calculatedusing the third EEG recording is <8.0 Hz or >13.0 Hz, a range of fIAFintrinsic alpha frequencies (fIAFs) of the first EEG recording, thesecond EEG recording and the third EEG recording is calculated, whereinif the range is <2.0 Hz, then the mean value of the final intrinsicalpha frequencies (fIAFs) of the first EEG recording, the second EEGrecording and the third EEG recording is determined to be the Validintrinsic alpha frequency (vIAF). In some embodiments, if the finalintrinsic alpha frequency (fIAF) of the EEG is from 8.0 Hz to 13.0 Hzand the standard deviation (SD) of the N epoch IAF values is <0.75 Hz,the final intrinsic alpha frequency (fIAF) is determined to be a validintrinsic alpha frequency (vIAF). In some embodiments, if a standarddeviation (SD) of the N epoch IAF values ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) is <8.0 Hz or >13.0 Hz, then a secondEEG recording is obtained and the method of claim 1 is repeated usingthe second EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the second EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the second EEG readingis <8.0 Hz or >13.0 Hz, then a third EEG recording is obtained and themethod of claim 1 is repeated using the third EEG recording in place ofthe first EEG recording. In some embodiments, if a standard deviation(SD) of the N epoch IAF values calculated using the third EEG reading≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) calculatedusing the third EEG reading is <8.0 Hz or >13.0 Hz, then a fourth EEGrecording is obtained and the method of claim 1 is repeated using thefourth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the fourth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the fourth EEG readingis <8.0 Hz or >13.0 Hz, then a fifth EEG recording is obtained and themethod of claim 1 is repeated using the fifth EEG recording in place ofthe first EEG recording. In some embodiments, if a standard deviation(SD) of the N epoch IAF values calculated using the fifth EEG reading≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) calculatedusing the fifth EEG reading is <8.0 Hz or >13.0 Hz, then a sixth EEGrecording is obtained and the method of claim 1 is repeated using thesixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the sixth EEG readingis <8.0 Hz or >13.0 Hz, then a seventh EEG recording is obtained and themethod of claim 1 is repeated using the seventh EEG recording in placeof the first EEG recording. In some embodiments, if a standard deviation(SD) of the N epoch IAF values calculated using the seventh EEG reading≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) calculatedusing the seventh EEG reading is <8.0 Hz or >13.0 Hz, then a eighth EEGrecording is obtained and the method of claim 1 is repeated using theeighth EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic alpha frequency (fIAF) calculatedusing the third EEG recording is <8.0 Hz or >13.0 Hz or if the standarddeviation (SD) of the N epoch IAF values calculated using the third EEGreading ≥0.75 Hz, a range of fIAF intrinsic alpha frequencies (fIAFs) ofthe first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic alpha frequencies (fIAFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic alpha frequency (vIAF). In someembodiments, if the final intrinsic alpha frequency (fIAF) calculatedusing the eighth EEG recording is <8.0 Hz or >13.0 Hz or if the standarddeviation (SD) of the N epoch IAF values calculated using the eighth EEGreading ≥0.75 Hz, a range of fIAF intrinsic alpha frequencies (fIAFs) ofthe at least three of the first EEG recording, the second EEG recording,the third EEG recording, the fourth EEG recording, the fifth EEGrecording, the sixth EEG recording, the seventh EEG recording, theeighth EEG recording is calculated, wherein if the range is <2.0 Hz,then the mean value of the final intrinsic alpha frequencies (fIAFs) ofat least three of the first EEG recording, the second EEG recording, thethird EEG recording, the fourth EEG recording, the fifth EEG recording,the sixth EEG recording, the seventh EEG recording, the eighth EEGrecording is determined to be the Valid intrinsic alpha frequency(vIAF). In some embodiments, a channel intrinsic alpha frequency isdetermined for each channel in the frequency domain epoch (i), and areaveraged to generate the epoch intrinsic alpha frequency (m_(i)).

Disclosed herein, in various embodiments are methods of determining afinal intrinsic alpha frequency of a subject in a neuro-EEGsynchronization therapy comprising: applying an EEG discriminationroutine comprising: obtaining a multi-channel EEG recording in a timedomain; dividing the multi-channel EEG recording into a plurality ofepochs, each epoch comprising a corresponding data segment from eachchannel, and averaging the data segments in each epoch together, whereina total number of epochs is N; filtering the data segments of each epochusing a high-pass filter; converting each epoch into a frequency domainepoch (i); filtering each frequency domain epoch (i) using a smoothingfilter; calculating an epoch intrinsic alpha frequency (m_(i)) of eachfrequency domain epoch (i); calculating a mean (M) intrinsic alphafrequency (IAF) of all intrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,if |m_(I)−M|>0.5 Hz, removing the farthest frequency domain epoch(m_(I)), decrementing N, and returning to step g), or if |m_(I)−M|≤0.5Hz, continuing to next step; setting a final intrinsic alpha frequency(fIAF) equal to M; and outputting the final intrinsic alpha frequency(fIAF) to a user or to a device, wherein the device is configured toconduct the neuro-EEG synchronization therapy. In some embodiments, theepoch intrinsic alpha frequency (m_(i)) is generated by averagingchannel intrinsic alpha frequencies generated from the channels meetinginclusion criteria and averaged together, wherein the inclusion criteriacomprise: a greatest alpha power as compared to all other channels ofthe EEG recording; a lowest variance as compared to all other channelsof the EEG recording; or a highest Q-factor as compared to all otherchannels of the EEG recording.

Disclosed herein, in various embodiments are methods of determining afinal intrinsic alpha frequency of a subject in a neuro-EEGsynchronization therapy comprising: applying an EEG discriminationroutine comprising: obtaining a multi-channel EEG recording from an EEGsensor in a time domain; treating each channel separately, dividing eachchannel of the multi-channel EEG recording into a plurality of epochs,each epoch comprising a data segment from each channel, wherein a totalnumber of epochs for each channel is N; filtering the data segments ofeach epoch, of each channel, using a high-pass filter; converting eachepoch, of each channel, into a frequency domain epoch (i); filteringeach frequency domain epoch (i), of each channel, using a smoothingfilter; calculating an epoch intrinsic alpha frequency (m_(i)) of eachfrequency domain epoch (i) for each channel; calculating a mean (M)channel intrinsic alpha frequency (cIAF) of all intrinsic alphafrequencies (m_(i-N)) for each channel, wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean Mfor each channel, if |m_(I)−M|>0.5 Hz, removing the farthest frequencydomain epoch (m_(I)), decrementing N, and returning to step g), or if|m_(I)−M|≤0.5 Hz, continuing to next step; averaging the mean (M)channel intrinsic alpha frequency (cIAF) of all channels to determine afinal intrinsic alpha frequency (fIAF); setting a final intrinsic alphafrequency (fIAF) equal to M for the entire multi-channel EEG recording;and outputting the final intrinsic alpha frequency (fIAF) to a user orto a device, wherein the device is configured to conduct the neuro-EEGsynchronization therapy. In some embodiments, a single channel intrinsicalpha frequency (cIAF) of the multi-channel EEG recording comprises; afrequency band between 8.0 Hz-13.0 Hz; a standard deviation (SD) below0.75 Hz; the lowest (SD) of all the channel intrinsic alpha frequencies(cIAFs) of the multi-channel EEG recording; and the single channelintrinsic alpha frequency (cIAF) is selected as a representativeintrinsic alpha frequency (IAF) for the multi-channel EEG recording. Insome embodiments, the intrinsic channel alpha frequencies (cIAFs) of allchannels of the multi-channel EEG recording that are within a bandbetween 8.0 Hz-13.0 Hz and have a standard deviation (SD) below 0.75 Hz,are averaged together to obtain a representative intrinsic alphafrequency (IAF) of the multi-channel time domain EEG recording.

Disclosed herein, in various embodiments are methods of determining avalid intrinsic frequency of an EEG band of a subject in neuro-EEGsynchronization therapy comprising: applying an EEG discriminationroutine comprising: obtaining a first EEG recording in a time domain;dividing the first EEG recording into a plurality of epochs, wherein atotal number of epochs is N; filtering the data using a high-passfilter; converting each epoch into a frequency domain epoch (i);filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic frequency (m_(i)) in an EEG band of eachfrequency domain epoch (i); calculating a mean (M) intrinsic frequency(IF) in the EEG band of all epoch intrinsic frequencies (m_(i-N)),wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean, if|m_(I)−M|>0.5 Hz, removing the farthest frequency domain epoch (m_(I)),decrementing N, and returning to step g), or if |m_(I)−M|≤0.5 Hz,continuing to next step; setting a final intrinsic frequency (fIF) inthe EEG band equal to M; and outputting the final intrinsic frequency(fIF) in the EEG band to a user or device, wherein the device isconfigured to conduct the neuro-EEG synchronization therapy. In someembodiments, the EEG band comprises one or more selected from: an Alphaband; a Theta band; a Beta band; a Gamma band; and a Delta band. In someembodiments, the EEG recording length is 128 seconds. In someembodiments, the EEG recording is a single-channel recording. In someembodiments, the EEG recording is a multi-channel recording, wherein achannel intrinsic frequency (cIF) estimate is made for each channel inan epoch and averaged together, or wherein each channel is treatedseparately, generating a final intrinsic frequency (fIF) estimate foreach channel for the full EEG recording, and wherein final intrinsicfrequency estimates from each channel, as determined by step h), areaveraged together to generate a final intrinsic frequency (fIF). In someembodiments, a channel of the EEG recording comprises 16 epochs. In someembodiments, the calculated epoch intrinsic frequency (m_(i)) of the EEGcomprises a range that is at least: ±0.5 Hz outside a range of the EEGband; ±1.0 Hz outside the range of the EEG band; ±1.5 Hz outside therange of the EEG band; and ±2.0 Hz outside the range of the EEG band. Insome embodiments, the EEG recording comprises a sample rate of 128samples/sec. In some embodiments, the high-pass filter uses a 4^(th)order Butterworth IIR filter with the 3 dB cutoff set to 5.0 Hz. In someembodiments, the epoch intrinsic alpha frequency of each epoch (m_(i))is determined using a Fast Fourier Transform (FFT). In some embodiments,the Fast Fourier Transform (FFT) uses a resolution of 1024 points, whichresults in a 0.125 Hz resolution per bin from 0 Hz to 64 Hz. In someembodiments, the Fast Fourier Transform (FFT) is smoothed with anaveraging filter that averages 5 points±2 from the target. In someembodiments, if the standard deviation (SD) of the N epoch IF values≥0.75 Hz, a second EEG recording is obtained and the method of claim 35is repeated using the second EEG recording in place of the first EEGrecording. In some embodiments, if the standard deviation (SD) of the Nepoch IF values calculated using the second EEG recording is ≥0.75 Hz, athird EEG recording is obtained and the method of claim 35 is repeatedusing the third EEG recording in place of the first EEG recording. Insome embodiments, if the standard deviation (SD) of the N epoch IFvalues calculated using the third EEG recording is ≥0.75 Hz, a fourthEEG recording is obtained and the method of claim 35 is repeated usingthe fourth EEG recording in place of the first EEG recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the fourth EEG recording is ≥0.75 Hz, a fifth EEGrecording is obtained and the method of claim 35 is repeated using thefifth EEG recording in place of the first EEG recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the fifth EEG recording is ≥0.75 Hz, a sixth EEGrecording is obtained and the method of claim 35 is repeated using thesixth EEG recording in place of the first EEG recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG recording is ≥0.75 Hz, a seventh EEGrecording is obtained and the method of claim 35 is repeated using theseventh EEG recording in place of the first EEG recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the seventh EEG recording is ≥0.75 Hz, an eighth EEGrecording is obtained and the method of claim 35 is repeated using theeighth EEG recording in place of the first EEG recording. In someembodiments, if an eighth standard deviation (SD) of the N epoch IFvalues ≥0.75 Hz obtained using the eighth EEG recording, a range of fIFintrinsic frequencies (fIFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is calculated,wherein if the range is <2.0 Hz, then the mean value of the finalintrinsic frequencies (fIFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is determined to bethe Valid intrinsic frequency (vIF). In some embodiments, if a thirdstandard deviation (SD) of the N epoch IF values ≥0.75 Hz obtained usingthe third EEG recording, a range of fIF intrinsic frequencies (fIFs) ofthe first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic frequencies (fIFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic frequency (vIF). In someembodiments, if the final intrinsic frequency (fIF) of the EEG recordingis > a predetermined amount outside the EEG band, a second EEG recordingis obtained and the method of claim 35 is repeated using the second EEGrecording in place of the first EEG recording. In some embodiments, thepredetermined amount is: ±0.5 Hz; ±1.0 Hz; ±1.5 Hz; or ±2.0 Hz. In someembodiments, if the final intrinsic frequency (fIF) of the EEG recordingobtained using the second EEG recording is > the predetermined amountoutside the EEG band, a third EEG recording is obtained and the methodof claim 35 is repeated using the third EEG recording in place of thefirst EEG recording. In some embodiments, if the final intrinsicfrequency (fIF) of the EEG recording obtained using the third EEGrecording is > the predetermined amount outside the EEG band, a fourthEEG recording is obtained and the method of claim 35 is repeated usingthe fourth EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic frequency (fIF) of the EEG recordingobtained using the fourth EEG recording is > the predetermined amountoutside the EEG band, a fifth EEG recording is obtained and the methodof claim 35 is repeated using the fifth EEG recording in place of thefirst EEG recording. In some embodiments, if the final intrinsicfrequency (fIF) of the EEG recording obtained using the fifth EEGrecording is > the predetermined amount outside the EEG band, a sixthEEG recording is obtained and the method of claim 35 is repeated usingthe sixth EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic frequency (fIF) of the EEG recordingobtained using the sixth EEG recording is > the predetermined amountoutside the EEG band, a seventh EEG recording is obtained and the methodof claim 35 is repeated using the seventh EEG recording in place of thefirst EEG recording. In some embodiments, if the final intrinsicfrequency (fIF) of the EEG recording obtained using the seventh EEGrecording is > the predetermined amount outside the EEG band, an eighthEEG recording is obtained and the method of claim 35 is repeated usingthe eighth EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic frequency (fIF) calculated using thethird EEG recording is > the predetermined amount outside the EEG band,a range of fIF intrinsic frequencies (fIFs) of the first EEG recording,the second EEG recording and the third EEG recording is calculated,wherein if the range is <2.0 Hz, then the mean value of the finalintrinsic frequencies (fIFs) of the first EEG recording, the second EEGrecording and the third EEG recording is determined to be the Validintrinsic frequency (vIF). In some embodiments, if the final intrinsicfrequency (fIF) calculated using the third EEG recording is > thepredetermined amount outside the EEG band, a range of fIF intrinsicfrequencies (fIFs) of three or more of the first EEG recording, thesecond EEG recording, the third EEG recording, the fourth EEG recording,the fifth EEG recording, the sixth EEG recording, the seventh EEGrecording, and the eighth EEG recording is calculated, wherein if therange is <2.0 Hz, then the mean value of the final intrinsic frequencies(fIFs) of three of the first EEG recording, the second EEG recording,the third EEG recording, the fourth EEG recording, the fifth EEGrecording, the sixth EEG recording, the seventh EEG recording, and theeighth EEG recording is determined to be the Valid intrinsic frequency(vIF). In some embodiments, if a standard deviation (SD) of the N epochIF values ≥0.75 Hz, or if the final intrinsic frequency (fIF) is > apredetermined amount outside the EEG band, wherein the predeterminedamount is ±0.5 Hz, ±1.0 Hz, ±1.5 Hz, or ±2.0 Hz; then a second EEGrecording is obtained and the method of claim 35 is repeated using thesecond EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the second EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the second EEG reading is >the predetermined amount outside the EEG band, then a third EEGrecording is obtained and the method of claim 35 is repeated using thethird EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the third EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the third EEG reading is >the predetermined amount outside the EEG band, then a fourth EEGrecording is obtained and the method of claim 35 is repeated using thefourth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the fourth EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the fourth EEG reading is >the predetermined amount outside the EEG band, then a fifth EEGrecording is obtained and the method of claim 35 is repeated using thefifth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the fifth EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the fifth EEG reading is >the predetermined amount outside the EEG band, then a sixth EEGrecording is obtained and the method of claim 35 is repeated using thesixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the sixth EEG reading is >the predetermined amount outside the EEG band, then a seventh EEGrecording is obtained and the method of claim 35 is repeated using theseventh EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the seventh EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the seventh EEG reading is >the predetermined amount outside the EEG band, then a eighth EEGrecording is obtained and the method of claim 35 is repeated using theeighth EEG recording in place of the first EEG recording. In someembodiments, if the final intrinsic frequency (fIF) calculated using thethird EEG recording is > the predetermined amount outside the EEG band,or if the standard deviation (SD) of the N epoch IF values calculatedusing the third EEG reading ≥0.75 Hz, a range of fIF intrinsicfrequencies (fIFs) of the first EEG recording, the second EEG recordingand the third EEG recording is calculated, wherein if the range is <2.0Hz, then the mean value of the final intrinsic frequencies (fIFs) of thefirst EEG recording, the second EEG recording and the third EEGrecording is determined to be the Valid intrinsic frequency (vIF). Insome embodiments, if the final intrinsic frequency (fIF) calculatedusing the eighth EEG recording is > the predetermined amount outside theEEG band or if the standard deviation (SD) of the N epoch IF valuescalculated using the eighth EEG reading ≥0.75 Hz, a range of fIFintrinsic frequencies (fIFs) of the at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, the eighth EEG recording is calculated, whereinif the range is <2.0 Hz, then the mean value of the final intrinsicfrequencies (fIFs) of at least three of the first EEG recording, thesecond EEG recording, the third EEG recording, the fourth EEG recording,the fifth EEG recording, the sixth EEG recording, the seventh EEGrecording, the eighth EEG recording is determined to be the Validintrinsic frequency (vIF). In some embodiments, if the final intrinsicfrequency (fIF) is within the EEG band and the standard deviation (SD)of the N epoch IF values is <0.75 Hz, the final intrinsic frequency(fIF) is determined to be a valid intrinsic frequency (vIF). In someembodiments, a channel intrinsic frequency is determined for eachchannel in the frequency domain epoch (i), and are averaged to generatethe epoch intrinsic frequency (m_(i)). In some embodiments, an epochintrinsic frequency (m_(i)) is generated by averaging channel intrinsicfrequencies generated from the channels meeting inclusion criteria andaveraged together, wherein the inclusion criteria comprise: a greatestpower in the EEG band as compared to all other channels of the EEGrecording; a lowest variance as compared to all other channels of theEEG recording; or a highest Q-factor as compared to all other channelsof the EEG recording. In some embodiments, each channel from amulti-channel time domain EEG recording is treated separately andgenerates a channel intrinsic frequency (cIF) for each channel of themulti-channel time domain EEG recording, wherein a number of channelintrinsic frequencies (cIFs) is equal to the number of channels. In someembodiments, all channel intrinsic frequencies (cIFs) from amulti-channel time domain EEG recording are averaged together to obtaina representative intrinsic frequency (IF) of the multi-channel timedomain EEG recording. In some embodiments, a single channel intrinsicfrequency (cIF) of a multi-channel time domain EEG recording comprises:a standard deviation (SD) below 0.75 Hz; the lowest (SD) of all thechannel intrinsic frequencies (cIFs) of the multi-channel time domainEEG recording; and the single channel intrinsic frequency (cIF) isselected as a representative intrinsic frequency (IF) for themulti-channel time domain EEG recording. In some embodiments, thechannel intrinsic frequency (cIF) of all channels of a multi-channeltime domain EEG recording that have a standard deviation (SD) below 0.75Hz; are averaged together to obtain a representative intrinsic frequency(IF) of the multi-channel time domain EEG recording. Disclosed herein,in various embodiments, are computer-implemented systems for determiningan intrinsic alpha frequency of a subject comprising: an input deviceconfigured to receive a first time domain EEG recording of a subject,wherein the EEG recording is obtained from an EEG sensor external to thecomputer-implemented system; a digital processing device comprising anoperating system configured to perform executable instructions and amemory; a computer program including instructions executable by thedigital processing device configured to discriminate a valid intrinsicalpha frequency of at least one time domain EEG recording of a subjectcomprising a software module configured to: determine if the time domainEEG recording has a stable intrinsic alpha frequency (m_(i)) throughouta plurality of epochs, wherein a valid intrinsic alpha frequencycomprises: a standard deviation between the epochs <0.75 Hz, and a mean(M) of epoch intrinsic alpha frequencies (m_(i)) between 8.0 Hz to 13.0Hz, set a final intrinsic alpha frequency (fIAF) equal to M; output thefinal intrinsic alpha frequency (fIAF) to a device, or, label the firsttime domain EEG recording suspect, and continue to sequentially evaluatea plurality of subsequent time domain EEG recordings until a validintrinsic alpha frequency is be obtained from a subsequent time domainEEG recording, wherein the plurality of subsequent time domain EEGrecording are obtained from an EEG sensor external to thecomputer-implemented system. In some cases, a total number of timedomain EEG recordings is eight. In some cases, if the software moduleroutine cannot obtain a valid intrinsic alpha frequency within the firsttime domain EEG recording, a second time domain EEG recording or a thirdtime domain EEG recording, a range of epoch intrinsic alpha frequencies(m_(i)) of the first time domain EEG recording, the second time domainEEG recording and the third time domain EEG recording is calculated,wherein if the range is <2.0 Hz, the mean (M) of the first time domainEEG recording, the second time domain EEG recording and the third timedomain EEG recording is calculated and is set equal to the finalintrinsic alpha frequency (fIAF). In some cases, if the software moduleroutine cannot obtain a valid intrinsic alpha frequency within eighttime domain EEG recordings, the software module routine ends and outputsa message to a user that a valid intrinsic alpha frequency cannot befound. In some cases, the device is a Neuro-EEG Synchronization Therapy(NEST) device. In some cases, the device is configured to deliver lowamplitude stimulation at an intrinsic alpha frequency that is the sameas a patient's intrinsic alpha frequency.

Disclosed herein, in various embodiments are methods of quantitativelyanalyzing EEG recordings to obtain a valid Intrinsic Alpha Frequency ofa subject using a Neuro-EEG Synchronization Therapy (NEST) devicecomprising: obtaining a single 128-second time domain EEG recording froman EEG sensor external to the device; dividing the 128-second EEGrecording into sixteen eight-second epochs; converting each epoch into afrequency domain epoch (i); calculating an epoch intrinsic alphafrequency (m_(i)) for each frequency domain epoch (i); and successivelyeliminating the epoch intrinsic alpha frequencies (m_(i)) that arefarthest from a mean, until the remaining epoch intrinsic alphafrequencies (m_(i)) are all within 0.5 Hz of the mean; and outputting afinal intrinsic alpha frequency (fIAF) for the EEG recording that isequal to the mean value of the remaining epochs' epoch intrinsic alphafrequencies. In some cases, the final intrinsic alpha frequency (fIAF)is determined to be valid if a standard deviation of the epoch intrinsicalpha frequencies (m_(i)) from the epochs is <0.75 Hz and the finalintrinsic alpha frequency (fIAF) within the band of 8.0-13.0 Hz. In somecases, the final intrinsic alpha frequency (fIAF) is determined to besuspect if a standard deviation of the epoch intrinsic alpha frequencies(m_(i)) from the epochs is ≥0.75 Hz or the final intrinsic alphafrequency (fIAF) is outside the band of 8.0-13.0 Hz, and wherein asecond EEG recording is obtained to determine if a valid intrinsic alphafrequency (vIAF) can be determined by repeating the steps of claim 88replacing the single 128-second time domain EEG recording with thesecond EEG recording. In some cases, the final intrinsic alpha frequency(fIAF) using the second EEG recording is determined to be suspect if astandard deviation of the epoch intrinsic alpha frequencies (m_(i)) fromthe epochs is ≥0.75 Hz or the final intrinsic alpha frequency (fIAF) isoutside the band of 8.0-13.0 Hz, and wherein a third EEG recording isobtained to determine if the valid intrinsic alpha frequency (vIAF) canbe determined by repeating the steps of claim 88 replacing the single128-second time domain EEG recording with the third EEG recording. Insome cases, if the valid intrinsic alpha frequency (vIAF) cannot beobtained using the third EEG recording, a range of the final intrinsicalpha frequency (fIAF) values of the three previous EEG recordings iscalculated, and if the range of the previous three final intrinsic alphafrequency (fIAF) values is <2.0 Hz, then the valid Intrinsic AlphaFrequency (vIAF) is set to the mean of the three previous finalIntrinsic Alpha Frequencies (fIAFs). In some cases, determining thefarthest frequency domain epoch (m_(I)) from the mean M comprisescalculating an index (I) of the frequency domain epoch that is farthestfrom the mean (M), wherein I=Index(max_(i)|m_(i)−M|). In some cases,determining the farthest frequency domain epoch (m_(I)) from the mean Mcomprises calculating an index (I) of the frequency domain epoch that isfarthest from the mean (M), wherein I=Index(max_(i)|m_(i)−M|). In someembodiments, wherein determining a farthest frequency domain epoch(m_(I)) from the mean M comprises calculating an index (I) of thefrequency domain epoch that is farthest from the mean (M), whereinI=Index(max_(i)|m_(i)−M|).

As described above, an IAF estimate is created based on a frequencyanalysis of the EEG. The EEG recording is divided into 8-second epochs.An IAF estimate is made for each epoch, resulting in a number ofdiscreet epoch-IAF values. A routine performs successive pruning ofthese values by eliminating the farthest from the mean, until theremaining epoch-IAF values were all within 0.5 Hz of the mean. The finalIAF estimate for that EEG is equal to the mean value of the remainingepochs' IAFs.

In some embodiments, the first EEG recording length is 128 seconds. Insome embodiments, the first EEG recording is a single-channel recording.In some embodiments, the first EEG recording is a multi-channelrecording, wherein an IAF estimate is made for each channel in an epochand averaged together, or wherein each channel is treated separately,generating an IAF estimate for each channel for the full EEG recording,and wherein valid IAF estimates from each channel, as determined by thestep; determining a farthest frequency domain epoch (m_(I)) from themean M, if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)), decrementing N, and returning to step g), or if|m_(I)−M|≤0.5 Hz, are averaged together to generate a final IAF. In someembodiments, a channel of the first EEG recording initially comprises 16epochs. In some embodiments, the epoch intrinsic alpha frequency (m_(i))of each frequency domain epoch (i) is calculated from 7.0 Hz to 14.0 Hz.In some embodiments, the final intrinsic alpha frequency (fIAF) is from8.0 Hz to 13.0 Hz. In some embodiments, the first EEG recordingcomprises a sample rate of 128 samples/sec. In some embodiments, thehigh-pass filter comprises a 4^(th) order Butterworth IIR filter withthe 3 dB cutoff set to 5.0 Hz. In some embodiments, the epoch intrinsicalpha frequency of each epoch (m_(i)) is determined using a Fast FourierTransform (FFT). In some embodiments, the Fast Fourier Transform (FFT)uses a resolution of 1024 points, which results in a 0.125 Hz resolutionper bin from 0 Hz to 64 Hz. In some embodiments, the Fast FourierTransform (FFT) is smoothed with an averaging filter that averages the 5points±2 from the target.

As described above, a final IAF estimate for an EEG recording is equalto the mean value of the remaining epoch's IAFs (following successivepruning) In order to accomplish this, an IAF estimate of each epoch mustbe calculated. In the following example, a typical EEG is 128 secondsand is divided in 16 8-second epochs, and each single recorded EEG epochinput data is analyzed as follows. A filter is applied to the data ofthe epoch. The sample rate is 128 samples/sec. The filtering uses a4^(th) order Butterworth IIR filter with the 3 dB cutoff set to 5.0 Hz.Next the data is run through a Fast Fourier Transform (FFT) to convertthe data from a sequence to frequency. The FFT uses 1024 points, whichresults in a 0.125 Hz resolution per bin over the range of 0-64 Hz. Asingle smoothing filter is used on the FFT to remove spurious peaks.This is a simple averaging filter that averages the 5 points+/−2 fromthe target. The data is analyzed to determine the peak location of theFFT between 7.0 Hz and 14.0 Hz. The peak IAF estimate of the epoch isequal to the frequency of that peak.

It should be noted, the peak IAF estimates are found in the range from7.0-14.0 Hz. However, the Alpha band is 8.0-13.0 Hz. The EEGdiscrimination algorithm will label an IAF estimate as “suspect” if itis out of band. To determine if an estimate is out of band, the range tofind peak IAF estimates must be wider than the Alpha band. For thisexample of the algorithm a window 1.0 Hz outside the Alpha band waschosen. However, depending on the band being analyzed, a differentwindow may be chosen.

As noted previously, outliers are identified and discarded in order todetermine a final IAF estimate. Alpha waves tend to be bursty in an EEG,with large sections showing little to no alpha activity, followed by arhythmic section with significant alpha peaks. After sixteen 8-secondepochs have been processed to obtain 16 IAF estimates, the algorithmremoves outliers, which are most likely due to noise. A routine performssuccessive pruning of these values by eliminating the farthest from themean, until the remaining epoch-IAF values are all within 0.5 Hz of themean. The sequence below gives the specifics of the routine. In this, Nis the total number of remaining epochs after pruning. M is the mean ofthe IAFs for all remaining epochs. m_(i) is the IAF estimate for epochi. The routine is described as follows: Set N to 16; the mean of theIAFs for all remaining epochs is calculated using the following formula:

$M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}{m_{i}\text{:}}}}$Next, the Index, I, of the farthest epoch from the mean is calculated,wherein I=Index(max_(i)|m_(i)−M|); and If |m_(i)−M|>0.5 Hz, then thefarthest epoch is removed, the value N is decreased by 1, and theprocess is repeated by recalculating the mean of the IAFs for allremaining epochs, again using the formula:

$M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}{m_{i}.}}}$

This routine is repeated until the remaining epoch-IAF values are allwithin 0.5 Hz of the mean. Once this condition is met, the IAF estimatefor the EEG is set equal to M.

As described herein, the Index (I) is the frequency domain epoch number(1 . . . N) in any iteration of the time domain EEG. During pruning, thealgorithm finds the index (I) of the epoch (1 . . . N) where the epochIAF is farthest from the mean M. If this difference is greater than 0.5Hz, the epoch is discarded and N is decreased. For example, if onebegins with the following 16 epochs: (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16); and then find that epoch #6 is farthest from themean (i.e., I=6), and is also greater than 0.5 Hz, epoch #6 would bediscarded, so the new list will be: (1, 2, 3, 4, 5, ___ 7, 8, 9, 10, 11,12, 13, 14, 15, 16), and N is decreased by 1.

The remaining epochs are then renumbered, resulting in (1, 2, 3, 4, 5,6, 7, 8, 9, 10, 11, 12, 13, 14, 15). The routine performs successivepruning of these values until the remaining epoch-IAF values were allwithin 0.5 Hz of the mean. Quite conceivably, one could wind up removingthe same index in two iterations of the pruning routine. For example,utilizing the previous result: The 6^(th) epoch (Index=6) is again foundto be farthest from the mean. It is again removed: (1, 2, 3, 4, 5, ___7, 8, 9, 10, 11, 12, 13, 14, 15); and the remaining epochs are againrenumbered: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14). This processwould continue until the remaining epoch-IAF values were all within 0.5Hz of the mean.

The purpose of the discrimination routine is to find a stable,repeatable IAF. Such an IAF is referred to as a “Valid” IAF. If an EEGrecording results in a final IAF (fIAF) that is either highly variablethroughout the 16 epochs (standard deviation of the N epoch IAFs isgreater than or equal to 0.75 Hz), or the fIAF is out of band (8.0-13.0Hz), it is labeled as “suspect”, and another EEG may be required.

If the first EEG results in a Valid IAF, the routine ends and thetreatment frequency is set to that value. If not, a second EEG recordingis performed to see if that one results in a Valid IAF. If that IAF issuspect, a 3^(rd) EEG is recorded.

In some embodiments, if a standard deviation (SD) of the N epoch IAFvalues ≥0.75 Hz, a second EEG recording is obtained and the previouslydescribed method of determining a final intrinsic alpha frequency of asubject (using a first EEG recording) is repeated using the second EEGrecording in place of the first EEG recording. In some embodiments, if asecond standard deviation (SD) of the N epoch IAF values ≥0.75 Hzobtained using the second EEG recording, a third EEG recording isobtained and the previously described method of determining a finalintrinsic alpha frequency of a subject (using a first EEG recording) isrepeated using the third EEG recording in place of the first EEGrecording.

After the 3^(rd) EEG, an additional option is available to find a ValidIAF. It has been found that, even if the IAFs are highly variable(standard deviation of the 16 epochs is greater than or equal to 0.75Hz), many times the final IAFs of consecutive EEG recordings are stillclose to the same value. Therefore, after the 3^(rd) EEG, the range offIAF values of the previous 3 EEGs is calculated, and if that range isless than 2.0 Hz, then the Valid IAF is set to the mean of the 3 suspectfIAFs. In some embodiments, if a third standard deviation (SD) of the Nepoch IAF values ≥0.75 Hz obtained using the third EEG recording, arange of fIAF intrinsic alpha frequencies (fIAFs) of the first EEGrecording, the second EEG recording and the third EEG recording iscalculated, wherein if the range is <2.0 Hz, then the mean value of thefinal intrinsic alpha frequencies (fIAFs) of the first EEG recording,the second EEG recording and the third EEG recording is determined to bethe Valid intrinsic alpha frequency (vIAF).

In still other embodiments, if the final intrinsic alpha frequency(fIAF) is <8.0 Hz or >13.0 Hz, a second EEG recording is obtained andthe previously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe second EEG recording in place of the first EEG recording. In stillother embodiments, if the final intrinsic alpha frequency (fIAF)calculated using the second EEG recording is <8.0 Hz or >13.0 Hz, athird EEG recording is obtained and the previously described method ofdetermining a final intrinsic alpha frequency of a subject (using afirst EEG recording) is repeated using the third EEG recording in placeof the first EEG recording. In still other embodiments, if the finalintrinsic alpha frequency (fIAF) calculated using the third EEGrecording is <8.0 Hz or >13.0 Hz, a range of fIAF intrinsic alphafrequencies (fIAFs) of the first EEG recording, the second EEG recordingand the third EEG recording is calculated, wherein if the range is <2.0Hz, then the mean value of the final intrinsic alpha frequencies (fIAFs)of the first EEG recording, the second EEG recording and the third EEGrecording is determined to be the Valid intrinsic alpha frequency(vIAF). Still further, in other embodiments, if the final intrinsicalpha frequency (fIAF) of the EEG is from 8.0 Hz-13.0 Hz and thestandard deviation (SD) of the N epoch IAF values is <0.75 Hz, the finalintrinsic alpha frequency (fIAF) is determined to be a valid intrinsicalpha frequency (vIAF).

In some embodiments of the method of determining a final intrinsic alphafrequency of a subject; if a standard deviation (SD) of the N epoch IAFvalues ≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) is<8.0 Hz or >13.0 Hz, then a second EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe second EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the second EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the second EEG readingis <8.0 Hz or >13.0 Hz, then a third EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe third EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the third EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the third EEG readingis <8.0 Hz or >13.0 Hz, then a fourth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe fourth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the fourth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the fourth EEG readingis <8.0 Hz or >13.0 Hz, then a fifth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe fifth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the fifth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the fifth EEG readingis <8.0 Hz or >13.0 Hz, then a sixth EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe sixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the sixth EEG readingis <8.0 Hz or >13.0 Hz, then a seventh EEG recording is obtained and thepreviously described method of determining a final intrinsic alphafrequency of a subject (using a first EEG recording) is repeated usingthe seventh EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IAF valuescalculated using the seventh EEG reading ≥0.75 Hz, or if the finalintrinsic alpha frequency (fIAF) calculated using the seventh EEGreading is <8.0 Hz or >13.0 Hz, then a eighth EEG recording is obtainedand the previously described method of determining a final intrinsicalpha frequency of a subject (using a first EEG recording) is repeatedusing the eighth EEG recording in place of the first EEG recording. Insome embodiments, if the final intrinsic alpha frequency (fIAF)calculated using the third EEG recording is <8.0 Hz or >13.0 Hz or ifthe standard deviation (SD) of the N epoch IAF values calculated usingthe third EEG reading ≥0.75 Hz, a range of fIAF intrinsic alphafrequencies (fIAFs) of the first EEG recording, the second EEG recordingand the third EEG recording is calculated, wherein if the range is <2.0Hz, then the mean value of the final intrinsic alpha frequencies (fIAFs)of the first EEG recording, the second EEG recording and the third EEGrecording is determined to be the Valid intrinsic alpha frequency(vIAF). In still other embodiments, if the final intrinsic alphafrequency (fIAF) calculated using the eighth EEG recording is <8.0 Hzor >13.0 Hz or if the standard deviation (SD) of the N epoch IAF valuescalculated using the eighth EEG reading ≥0.75 Hz, a range of fIAFintrinsic alpha frequencies (fIAFs) of the at least three of the firstEEG recording, the second EEG recording, the third EEG recording, thefourth EEG recording, the fifth EEG recording, the sixth EEG recording,the seventh EEG recording, the eighth EEG recording is calculated,wherein if the range is <2.0 Hz, then the mean value of the finalintrinsic alpha frequencies (fIAFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, the eighth EEG recording is determined to be theValid intrinsic alpha frequency (vIAF).

In still other embodiments, if an 8^(th) EEG recording is performed anddoes not result in a Valid IAF, then the routine ends, and informs theuser that a Valid IAF cannot be found.

Due to the previously noted “bursty” nature of Alpha waves in an EEG, itshould be noted that the clinician should replace electrodes betweeneach EEG and check electrode placement and electrode impedance. Also,the clinician must speak to the subject before each EEG, reminding thesubject to relax, keep still, not move or open their eyes, clench theirjaw, or shift around as these activities may exacerbate the problem. Theflowchart in FIG. 1 provides an illustrative example of thisdiscrimination routine.

Also as noted earlier, it has been shown that a magnetic field frequencywithin 1.0 Hz of the patient's IAF is required to obtain a benefit fromNEST therapy. Therefore, the discrimination algorithm should be appliedin order to find a valid IAF for each subject, and then exclude from theanalysis those whose valid IAF is more than 1.0 Hz from the treatmentfrequency. In a trial, the baseline EEG can be used to determine themagnetic field frequency. However, weekly single-channel EEGs may alsobe recorded for each subject in a trial. A subject's natural IAF doesnot change significantly over time, and no evidence has been found fromEEG evaluation that IAF values would change week to week during atreatment protocol.

The flowchart in FIG. 2 is a representative description of a process ofusing the EEG Discrimination algorithm from FIG. 1 as aninclusion/exclusion criterion for the clinical trial. In a trial, weeklyEEGs are recorded for each subject. The magnetic field frequency isbased on each subject's baseline EEG. The EEG Discrimination algorithmdetermines a valid IAF for the subject, using subsequent EEGs ifnecessary. If a valid IAF cannot be found, the subject is excluded. If avalid IAF is found which is not within 1.0 Hz of the treatment frequency(Tx Freq), then the subject is excluded as well. Otherwise, the subjectis included in the analysis. The methodology that was used to comparethe treatment frequency (Tx Freq), equal to the baseline EEG IAF value,with all recorded EEGs (up to 8) to determine if a subject had a validbaseline IAF, and includes the subject if the valid IAF is within 1.0 Hzof the Tx Freq. Final determination of a valid IAF resulted in asubject's inclusion or exclusion from eligibility for a clinical trial.

Provided herein is a method of determining a final intrinsic alphafrequency of a subject comprising applying an EEG discrimination routinecomprising: obtaining a multi-channel EEG recording in a time domain;dividing the multi-channel EEG recording into a plurality of epochs,each epoch comprising a corresponding data segment from each channel,and averaging the data segments in each epoch together, wherein a totalnumber of epochs is N; filtering the data segments of each epoch using ahigh-pass filter; converting each epoch into a frequency domain epoch(i); filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic alpha frequency (m_(i)) of each frequencydomain epoch (i); calculating a mean (M) intrinsic alpha frequency (IAF)of all intrinsic alpha frequencies (m_(i-N)), wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean M,wherein, i) if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)), decrementing N, and returning to step g), or, ii) if|m_(I)−M|≤0.5 Hz, continuing to next step; setting a final intrinsicalpha frequency (fIAF) equal to M; and outputting the final intrinsicalpha frequency (fIAF) to a user or to a device.

In some embodiments, a channel intrinsic alpha frequency (cIAF) isdetermined for each channel in the frequency domain epoch (i) of amulti-channel EEG recording, and they are averaged together to generatethe epoch intrinsic alpha frequency (m_(i)). In some embodiments, theepoch intrinsic alpha frequency (m_(i)) is generated by averagingchannel intrinsic alpha frequencies generated from the channels meetinginclusion criteria and averaged together, wherein the inclusion criteriacomprise: i) a greatest alpha power as compared to all other channels ofthe EEG recording; ii) a lowest variance as compared to all otherchannels of the EEG recording; or iii) a highest Q-factor as compared toall other channels of the EEG recording

Provided herein is a method of determining a final intrinsic alphafrequency of a subject comprising applying an EEG discrimination routinecomprising: obtaining a multi-channel EEG recording in a time domain;treating each channel separately, dividing each channel of multi-channelEEG recording into a plurality of epochs, each epoch comprising asegment data, from each channel, wherein a total number of epochs foreach channel is N; filtering the data segments of each epoch, of eachchannel, using a high-pass filter; converting each epoch, of eachchannel, into a frequency domain epoch (i); filtering each frequencydomain epoch (i), of each channel, using a smoothing filter; calculatingan epoch intrinsic alpha frequency (m_(i)) of each frequency domainepoch (i) for each channel; calculating a mean (M) channel intrinsicalpha frequency (cIAF) of all intrinsic alpha frequencies (m_(i-N)) foreach channel, wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining a farthest frequency domain epoch (m_(I)) from the mean Mfor each channel, wherein, i) if |m_(I)−M|>0.5 Hz, removing the farthestfrequency domain epoch (m_(I)), decrementing N, and returning to stepg), or ii) if |m_(I)−M|≤0.5 Hz, continuing to next step; averaging themean (M) channel intrinsic alpha frequency (cIAF) of all channels todetermine a final intrinsic alpha frequency (fIAF); setting a finalintrinsic alpha frequency (fIAF) equal to M for the entire multi-channelEEG recording; and outputting the final intrinsic alpha frequency (fIAF)to a user or to a device.

In some embodiments, a single channel intrinsic alpha frequency (cIAF)of the multi-channel EEG recording comprises; a frequency band between8.0 Hz-13.0 Hz; a standard deviation (SD) below 0.75 Hz; the lowest (SD)of all the channel intrinsic alpha frequencies (cIAFs) of themulti-channel EEG recording; and the single channel intrinsic alphafrequency (cIAF) is selected as a representative intrinsic alphafrequency (IAF) for the multi-channel EEG recording.

In some embodiments, the intrinsic channel alpha frequencies (cIAFs) ofall channels of the multi-channel EEG recording that are within a bandbetween 8.0 Hz-13.0 Hz and have a standard deviation (SD) below 0.75 Hz;are averaged together to obtain a representative intrinsic alphafrequency (IAF) of the multi-channel time domain EEG recording.

In some embodiments, a multiple-channel time domain EEG recording may beused, wherein different options exist for determining the intrinsicalpha frequency (IAF). In one embodiment, each channel from the firstmulti-channel time domain EEG recording is treated separately andgenerates a channel intrinsic alpha frequency (cIAF) for each channel ofthe full multi-channel time domain EEG recording, wherein a number ofchannel intrinsic alpha frequencies (cIAFs) is equal to the number ofchannels from the first multi-channel time domain EEG recording. In someembodiments, all channel intrinsic alpha frequencies (cIAFs) from thefirst multi-channel time domain EEG recording are averaged together toobtain a representative intrinsic alpha frequency (IAF) of themulti-channel time domain EEG recording. In some embodiments a singlechannel alpha frequency (cIAF) of the first multi-channel time domainEEG recording is within a band between 8.0 Hz-13.0 Hz; has a standarddeviation (SD) below 0.75 Hz; has the lowest (SD) of all the channelintrinsic alpha frequencies (cIAFs) of the multi-channel time domain EEGrecording; and is selected as a representative intrinsic alpha frequency(IAF) of the multi-channel time domain EEG recording. Still further, thechannel intrinsic alpha frequency (cIAF) of all channels of the firstmulti-channel time domain EEG recording that are within a band between8.0 Hz-13.0 Hz; and have a standard deviation (SD) below 0.75 Hz; areaveraged together to obtain a representative intrinsic alpha frequency(IAF) of the multi-channel time domain EEG recording.

Provided herein is a method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject comprising: applying an EEGdiscrimination routine comprising: obtaining a first EEG recording in atime domain; dividing the first EEG recording into a plurality ofepochs, wherein a total number of epochs is N; filtering the data usinga high-pass filter (to reduce the influence of heartbeat and lowfrequency noise); converting each epoch into a frequency domain epoch(i); filtering each frequency domain epoch (i) using a smoothing filter;calculating an epoch intrinsic frequency (m_(i)) in an EEG band of eachfrequency domain epoch (i); calculating a mean (M) intrinsic frequency(IF) in the EEG band of all epoch intrinsic frequencies (m_(i-N)),wherein

${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$determining the farthest frequency domain epoch (m_(I)) from the mean,wherein if |m_(I)−M|>0.5 Hz, removing the farthest frequency domainepoch (m_(I)) decrementing N, and returning to the step for calculatinga mean (M) intrinsic frequency (IF) in the band of all epoch intrinsicfrequencies, or if |m_(I)−M|≤0.5 Hz, then; continue to the next step forsetting a final intrinsic frequency (fIF) equal to M; and outputting thefinal intrinsic frequency (fIF) in the EEG band equal to M; andoutputting the final intrinsic frequency (fIF) in the EEG band to a useror device. In some embodiments, wherein determining a farthest frequencydomain epoch (m_(I)) from the mean M comprises determining an index (I)of the frequency domain epoch that is farthest from the mean (M),wherein I=Index(max_(i)|m_(i)−M|). In some embodiments, the EEG bandcomprises: an Alpha band; a Theta band; a Beta band; a Gamma band; and aDelta band. In some embodiments, the EEG recording length is 128seconds. In some embodiments, the EEG recording is a single-channelrecording. In some embodiments, the EEG recording is a multi-channelrecording. In some embodiments the EEG is a multi-channel recording,wherein a channel intrinsic frequency (cIF) estimate may be made foreach channel in an epoch and averaged together, or wherein each channelis treated separately, generating a final intrinsic frequency (fIF)estimate for each channel for the full EEG recording, and wherein finalintrinsic frequency estimates from each channel, as determined by steph), are averaged together to generate a final intrinsic frequency (fIF).In some embodiments, a channel of the EEG comprises 16 epochs. In someembodiments, the calculated epoch intrinsic frequency (m_(i)) of the EEGcomprises a range that is at least: ±0.5 Hz outside the range of the EEGband; ±1.0 Hz outside the range of the EEG band; ±1.5 Hz outside therange of the EEG band; and ±2.0 Hz outside the range of the EEG band. Insome embodiments, the EEG recording comprises a sample rate of 128samples/sec. In some embodiments, the high-pass filter uses a 4^(th)order Butterworth IIR filter with the 3 dB cutoff set to 5.0 Hz. In someembodiments, the epoch intrinsic frequency of each epoch (m_(i)) isdetermined using a Fast Fourier Transform (FFT). In some embodiments,the Fast Fourier Transform (FFT) uses a resolution of 1024 points, whichresults in a 0.125 Hz resolution per bin from 0 Hz to 64 Hz. In someembodiments, the Fast Fourier Transform (FFT) is smoothed with anaveraging filter that averages 5 points±2 from the target. In someembodiments, if the standard deviation (SD) of the N epoch IF value is≥0.75 Hz, a second EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe second EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the second EEG recording is ≥0.75 Hz, a third EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the third EEG recording in placeof the first recording. In some embodiments, if the standard deviation(SD) of the N epoch IF values calculated using the third EEG recordingis ≥0.75 Hz, a fourth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe fourth EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the fourth EEG recording is ≥0.75 Hz, a fifth EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the fifth EEG recording in placeof the first recording. In some embodiments, if the standard deviation(SD) of the N epoch IF values calculated using the fifth EEG recordingis ≥0.75 Hz, a sixth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe sixth EEG recording in place of the first recording. In someembodiments, if the standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG recording is ≥0.75 Hz, a seventh EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the seventh EEG recording inplace of the first recording. In some embodiments, if the standarddeviation (SD) of the N epoch IF values calculated using the seventh EEGrecording is ≥0.75 Hz, an eighth EEG recording is obtained and thepreviously described method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject (using a first EEG recording) isrepeated using the eighth EEG recording in place of the first recording.In still other embodiments, if the eighth standard deviation (SD) of theN epoch IF values is ≥0.75 Hz obtained using the eighth EEG recording, arange of final intrinsic frequencies (fIFs) of at least three of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, and the eighth EEG recording iscalculated, wherein if the range is <2.0 Hz, then the mean value of thefinal intrinsic frequencies (fIFs) of at least three of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is determined to bethe Valid intrinsic frequency (vIF). In some embodiments, if a thirdstandard deviation (SD) of the N epoch IF values ≥0.75 Hz obtained usingthe third EEG recording, a range of final intrinsic frequencies (fIFs)of the first EEG recording, the second EEG recording and the third EEGrecording is calculated, wherein if the range is <2.0 Hz, then the meanvalue of the final intrinsic frequencies (fIFs) of the first EEGrecording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic frequency (vIF). In someembodiments of the method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject, if the final intrinsic frequency(fIF) of the EEG recording is > a predetermined amount outside the EEGband, a second EEG recording is obtained and the method of determining avalid intrinsic frequency (vIF) of an EEG band of a subject is repeatedusing the second EEG recording in place of the first EEG recording. Insome embodiments, the predetermined amount is: ±0.5 Hz; ±1.0 Hz; ±1.5Hz; or ±2.0 Hz. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the second EEG recording is >the predetermined amount outside the EEG band, a third EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the third EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the third EEG recording is >the predetermined amount outside the EEG band, a fourth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the fourth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the fourth EEG recording is >the predetermined amount outside the EEG band, a fifth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the fifth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the fifth EEG recording is >the predetermined amount outside the EEG band, a sixth EEG recording isobtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the sixth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the sixth EEG recording is >the predetermined amount outside the EEG band, a seventh EEG recordingis obtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the seventh EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) of the EEG recording obtained using the seventh EEG recording is >the predetermined amount outside the EEG band, an eighth EEG recordingis obtained and the previously described method of determining a validintrinsic frequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the eighth EEG recording in place of thefirst recording. In some embodiments, if the final intrinsic frequency(fIF) calculated using the third EEG recording is > the predeterminedamount outside the EEG band, a range of final intrinsic frequencies(fIFs) of the first EEG recording, the second EEG recording and thethird EEG recording is calculated, wherein if the range is <2.0 Hz, thenthe mean value of the final intrinsic frequencies (fIFs) of the firstEEG recording, the second EEG recording and the third EEG recording isdetermined to be the Valid intrinsic frequency (vIF). In someembodiments, if the final intrinsic frequency (fIF) calculated using thethird EEG recording is > the predetermined amount outside the EEG band,a range of final intrinsic frequencies (fIFs) of three or more of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, and the eighth EEG recording iscalculated, wherein if the range is <2.0 Hz, then the mean value of thefinal intrinsic frequencies (fIFs) of the three or more of the first EEGrecording, the second EEG recording, the third EEG recording, the fourthEEG recording, the fifth EEG recording, the sixth EEG recording, theseventh EEG recording, and the eighth EEG recording is determined to bethe Valid intrinsic frequency (vIF).

In some embodiments of the method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject, if a standard deviation(SD) of the N epoch IF values ≥0.75 Hz, or if the final intrinsicfrequency (fIF) is > a predetermined amount outside the EEG band,wherein the predetermined amount is ±0.5 Hz, ±1.0 Hz, ±1.5 Hz, or ±2.0Hz; then a second EEG recording is obtained and the previously describedmethod of determining a valid intrinsic frequency (vIF) of an EEG bandof a subject (using a first EEG recording) is repeated using the secondEEG recording in place of the first EEG recording. In some embodiments,if a standard deviation (SD) of the N epoch IF values calculated usingthe second EEG reading ≥0.75 Hz, or if the final intrinsic frequency(fIF) calculated using the second EEG reading is > the predeterminedamount outside the EEG band, then a third EEG recording is obtained andthe previously described method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject (using a first EEGrecording) is repeated using the third EEG recording in place of thefirst EEG recording. In some embodiments, if a standard deviation (SD)of the N epoch IF values calculated using the third EEG reading ≥0.75Hz, or if the final intrinsic frequency (fIF) calculated using the thirdEEG reading is > the predetermined amount outside the EEG band, then afourth EEG recording is obtained and the previously described method ofdetermining a valid intrinsic frequency (vIF) of an EEG band of asubject (using a first EEG recording) is repeated using the fourth EEGrecording in place of the first EEG recording. In some embodiments, if astandard deviation (SD) of the N epoch IF values calculated using thefourth EEG reading ≥0.75 Hz, or if the final intrinsic frequency (fIF)calculated using the fourth EEG reading is > the predetermined amountoutside the EEG band, then a fifth EEG recording is obtained and thepreviously described method of determining a valid intrinsic frequency(vIF) of an EEG band of a subject (using a first EEG recording) isrepeated using the fifth EEG recording in place of the first EEGrecording. In some embodiments, if a standard deviation (SD) of the Nepoch IF values calculated using the fifth EEG reading ≥0.75 Hz, or ifthe final intrinsic frequency (fIF) calculated using the fifth EEGreading is > the predetermined amount outside the EEG band, then a sixthEEG recording is obtained and the method of claim 35 is repeated usingthe sixth EEG recording in place of the first EEG recording. In someembodiments, if a standard deviation (SD) of the N epoch IF valuescalculated using the sixth EEG reading ≥0.75 Hz, or if the finalintrinsic frequency (fIF) calculated using the sixth EEG reading is >the predetermined amount outside the EEG band, then a seventh EEGrecording is obtained and the previously described method of determininga valid intrinsic frequency (vIF) of an EEG band of a subject (using afirst EEG recording) is repeated using the seventh EEG recording inplace of the first EEG recording. In some embodiments, if a standarddeviation (SD) of the N epoch IF values calculated using the seventh EEGreading ≥0.75 Hz, or if the final intrinsic frequency (fIF) calculatedusing the seventh EEG reading is > the predetermined amount outside theEEG band, then a eighth EEG recording is obtained and the previouslydescribed method of determining a valid intrinsic frequency (vIF) of anEEG band of a subject (using a first EEG recording) is repeated usingthe eighth EEG recording in place of the first EEG recording. In stillfurther embodiments, if the final intrinsic frequency (fIF) calculatedusing the third EEG recording is > the predetermined amount outside theEEG band, or if the standard deviation (SD) of the N epoch IF valuescalculated using the third EEG reading ≥0.75 Hz, a range of finalintrinsic frequencies (fIFs) of the first EEG recording, the second EEGrecording and the third EEG recording is calculated, wherein if therange is <2.0 Hz, then the mean value of the final intrinsic frequencies(fIFs) of the first EEG recording, the second EEG recording and thethird EEG recording is determined to be the Valid intrinsic frequency(vIF). Further still, in some embodiments, if the final intrinsicfrequency (fIF) calculated using the eighth EEG recording is > thepredetermined amount outside the EEG band or if the standard deviation(SD) of the N epoch IF values calculated using the eighth EEG reading≥0.75 Hz, a range of final intrinsic frequencies (fIFs) of the at leastthree of the first EEG recording, the second EEG recording, the thirdEEG recording, the fourth EEG recording, the fifth EEG recording, thesixth EEG recording, the seventh EEG recording, the eighth EEG recordingis calculated, wherein if the range is <2.0 Hz, then the mean value ofthe final intrinsic frequencies (fIFs) of the at least three of thefirst EEG recording, the second EEG recording, the third EEG recording,the fourth EEG recording, the fifth EEG recording, the sixth EEGrecording, the seventh EEG recording, the eighth EEG recording isdetermined to be the Valid intrinsic frequency (vIF).

In some embodiments of the method of determining a valid intrinsicfrequency (vIF) of an EEG band of a subject, if the final intrinsicfrequency (fIF) is within the EEG band and the standard deviation (SD)of the N epoch IF value is <0.75 Hz, the final intrinsic frequency (fIF)is determined to be a valid intrinsic frequency (vIF). In someembodiments, a channel intrinsic frequency (cIF) is determined for eachchannel in the frequency domain epoch (i), and they are averaged togenerate the epoch intrinsic frequency (m_(i)). In some embodiments, anepoch intrinsic frequency (m_(i)) is generated by averaging channelintrinsic frequencies (cIFs) generated from the channels meetinginclusion criteria and averaged together, wherein the inclusion criteriacomprise: a greatest power in the EEG band as compared to all otherchannels of the EEG recording; a lowest variance as compared to allother channels of the EEG recording; or a highest Q-factor as comparedto all other channels of the EEG recording.

Further still, in some embodiments, each channel from a multi-channeltime domain EEG recording is treated separately and generates a channelintrinsic frequency (cIF) for each channel of the full multi-channeltime domain EEG recording, wherein a number of channel intrinsicfrequencies (cIFs) is equal to the number of channels from themulti-channel time domain EEG recording. In other embodiments, allchannel intrinsic frequencies (cIFs) from a multi-channel time domainEEG recording are averaged together to obtain a representative intrinsicfrequency (IF) of the multi-channel time domain EEG recording. In someembodiments, the channel intrinsic frequency (cIF) of a single channelof a multi-channel time domain EEG recording comprises: a standarddeviation (SD) below 0.75 Hz; the lowest (SD) of all the channelintrinsic frequencies (cIFs) of the multi-channel time domain EEGrecording; and is selected as a representative intrinsic frequency (IF)of the multi-channel time domain EEG recording. In still otherembodiments, all channel intrinsic frequencies (cIFs) of channels of amulti-channel time domain EEG recording that have a standard deviation(SD) below 0.75 Hz; are averaged together to obtain a representativeintrinsic frequency (IF) of the multi-channel time domain EEG recording.

Use of the Invention

To use the invention, an EEG is recorded from the patient. The algorithmwill generate an IAF estimate for the patient and label it as either“valid” or “suspect”, depending on whether or not it is in band andstable. If the IAF is valid, then the procedure ends. If the IAF issuspect, then another EEG may need to be recorded. This processcontinues until either a valid IAF is generated or 8 EEG recordings havebeen completed. If the subject reaches 8 EEGs without a valid IAF, thesubject is informed that he or she does not have an EEG that contains adetectable alpha frequency.

A single-channel EEG or multiple-channel EEG may be used. For amultiple-channel EEG, different options exist for determining the IAF ofan EEG recording.

In one aspect, an IAF estimate may be made for each channel in an epochand then averaged together. IAF estimates from all channels for a singleepoch could be averaged together.

Alternately, IAF estimates only from channels whose EEGs meet a specificcriteria could be averaged, such as: Greatest alpha power; Lowestvariance; or Highest Q factor.

In one aspect, each channel is treated separately, generating its ownIAF estimate for the full recording. In the end, a number of IAFestimates exist equal to the number of channels. Afterward, valid IAFestimates from the channels can be averaged together for a final IAFestimate for the EEG recording.

Alternately, the channel that is in band with the lowest standarddeviation could be used as the representative channel for the EEGrecording.

Alternately, all channels which are in band with a standard deviationbelow 0.75 Hz could be averaged together to get an IAF estimate for thefull recording.

In a preferred aspect, the intrinsic frequency of the Alpha band iscalculated. Alternately, the intrinsic frequency of other EEG bandscould be calculated. These include: the Theta band; the Beta band; theGamma band; and the Delta band.

In the part of the routine to find peak IAF of a single epoch, thewindow to find the peak is 1.0 Hz outside the EEG band of interest. Thedecision of the window width may be different depending on the EEG band,the patient, or the therapy being provided. In one aspect, the window is0.5 Hz outside the EEG band of interest. In one aspect, the window is1.5 Hz outside the EEG band of interest. In one aspect, the window is2.0 Hz outside the EEG band of interest.

There were several variables that can be chosen for the algorithm, whichmay change based on the EEG band, the patient, or the therapy. Some ofthese include: EEG recording length (Preferred: 128 seconds); Samplerate (Preferred: 128 Hz); Filtering settings (filter type, order, cutofffrequency), wherein a preferred filtering includes: Butterworth, 4^(th)order, 5.0 Hz.; FFT resolution (Preferred: 1024 point), (with an exampleof the output illustrated by FIG. 4); Averaging filter settings(Preferred: +/−2 samples); Number of epochs, (Preferred=16, asillustrated in FIG. 3); Number of channels (Preferred: 1); Distance fromthe mean threshold to remove epochs (Preferred: 0.5 Hz); Standarddeviation threshold to label an IAF as suspect (Preferred: 0.75 Hz); thenumber of EEG recordings before the additional option to average anumber of previous EEGs in finding a valid IAF (Preferred: 3); thenumber of EEG recordings averaged to find a valid IAF (Preferred: 3);and, the number of EEG recordings without a valid IAF before thealgorithm informs the user that none can be found (Preferred: 8).

Validation of the Discrimination Algorithm—Example 1

The EEG recordings from a clinical trial database formed the test setfor a validation of the algorithm (See ClinicalTrials.gov registration#NCT01370733). The validation was performed to ensure that at least 90%of subjects in the test set were found to have a recalculated IAFestimate that is within 1.0 Hz away from the treatment frequency used ina clinical trial. In addition, an expert qualitative analysis wasperformed on those subjects whose recalculated IAF estimates were morethan 1.0 Hz away from the baseline estimate.

229 subjects were evaluated out of the total of 231. Two subjects had noEEGs available due to an error made when downloading the EEGs. Five ofthe subjects did not have a stable EEG to get a valid IAF.

Of the 229 subjects, 22 either had a recalculated IAF that was greaterthan 1.0 Hz from the baseline IAF or were unable to determine a validIAF. It was noted that these were the same subjects that were previouslyexcluded from the “per protocol” analysis of a clinical trial. In themajority of the remaining subjects, the new algorithm produced an IAFvalue that was exactly the same as original treatment frequency used inthe clinical study. Result: (22 inaccurate IAFs)/(229 subjects)=9.6%,which is less than 10.0%. PASS.

Provided herein is a device comprising a computer-implemented systemconfigured to discriminate a valid intrinsic alpha frequency of at leastone time domain EEG recording of a subject comprising a software modulewith a routine configured to: evaluate a first time domain EEG recordingof a subject; determine if the time domain EEG recording has a stableintrinsic alpha frequency (m_(i)) throughout a plurality of epochswherein a valid intrinsic alpha frequency comprises; a standarddeviation between the epochs is <0.75 Hz, and a mean (M) of epochintrinsic alpha frequencies (m_(i)) between 8.0 Hz to 13.0 Hz; set afinal intrinsic alpha frequency (fIAF) equal to M; and output the finalintrinsic alpha frequency (fIAF) to the device; or, label the first timedomain EEG recording suspect; and continue to sequentially evaluate aplurality of subsequent time domain EEG recordings until a validintrinsic alpha frequency can be obtained from a subsequent time domainEEG recording. In some embodiments of the computer implemented system, atotal number of time domain EEG recordings is eight. In some embodimentsof the computer implemented system, if the software module routinecannot obtain a valid intrinsic alpha frequency within the first timedomain EEG recording, a second time domain EEG recording or a third timedomain EEG recording, a range of epoch intrinsic alpha frequencies(m_(i)) of the first time domain EEG recording, the second time domainEEG recording and the third time domain EEG recording is calculated,wherein if the range is <2.0 Hz, the mean (M) of the first time domainEEG recording, the second time domain EEG recording and the third timedomain EEG recording is calculated and is set equal to the finalintrinsic alpha frequency (fIAF). In some embodiments of the computerimplemented system, if the software module routine cannot obtain a validintrinsic alpha frequency within eight time domain EEG recordings, thesoftware module routine ends and outputs a message to a user that avalid intrinsic alpha frequency cannot be found. In some embodiments,the device comprises a Neuro-EEG Synchronization Therapy (NEST) device.In some embodiments, the device is configured to deliver low amplitudestimulation at an intrinsic alpha frequency that is the same as apatient's intrinsic alpha frequency.

Provided herein is a method of quantitatively analyzing EEG recordingsto obtain a valid Intrinsic Alpha Frequency of a subject using aNeuro-EEG Synchronization Therapy (NEST) device comprising: obtaining asingle 128-second time domain EEG recording; dividing the 128-second EEGrecording into sixteen eight-second epochs; converting each epoch into afrequency domain epoch (i); calculating an epoch intrinsic alphafrequency (m_(i)) for each frequency domain epoch (i); successivelyeliminating the epoch intrinsic alpha frequencies (m_(i)) that arefarthest from a mean, until the remaining epoch intrinsic alphafrequencies (m_(i)) are all within 0.5 Hz of the mean; and outputting afinal intrinsic alpha frequency (fIAF) for the EEG recording that isequal to the mean value of the remaining epochs' epoch intrinsic alphafrequencies. In some embodiments, the final intrinsic alpha frequency(fIAF) is determined to be valid if the standard deviation of the epochintrinsic alpha frequencies (m_(i)) from the epochs is <0.75 Hz and thefinal intrinsic alpha frequency (fIAF) is within the band of 8.0-13.0Hz. In some embodiments, the final intrinsic alpha frequency (fIAF) isdetermined to be suspect if a standard deviation of the epoch intrinsicalpha frequencies (m_(i)) from the epochs is ≥0.75 Hz or the finalintrinsic alpha frequency (fIAF) is outside the band of 8.0-13.0 Hz, andwherein a second EEG is recorded is obtained to determine if a validintrinsic alpha frequency (vIAF) can be determined as definedpreviously, by replacing the single 128-second time domain EEG recordingwith the second EEG recording. In some embodiments, the final intrinsicalpha frequency (fIAF) using the second EEG recording is determined tobe suspect if a standard deviation of the epoch intrinsic alphafrequencies (m_(i)) from the epochs is ≥0.75 Hz or the final intrinsicalpha frequency (fIAF) is outside the band of 8.0-13.0 Hz, and wherein athird EEG recording is obtained to determine if the valid intrinsicalpha frequency (vIAF) can be determined as defined previously, byreplacing the single 128-second time domain EEG recording with the thirdEEG recording. In some embodiments, if the valid intrinsic alphafrequency (vIAF) cannot be obtained using the third EEG recording, arange of the final intrinsic alpha frequency (fIAF) values of the threeprevious EEG recordings is calculated, and if the range of the previousthree final intrinsic alpha frequency (fIAF) values is <2.0 Hz, then thevalid Intrinsic Alpha Frequency (vIAF) is set to the mean of the threeprevious final Intrinsic Alpha Frequencies (fIAFs).

In some embodiments of the method of determining a final intrinsic alphafrequency of a subject, wherein determining the farthest frequencydomain epoch (m_(I)) from the mean M comprises calculating an index (I)of the frequency domain epoch that is farthest from the mean (M),wherein I=Index(max_(i)|m_(i)−M|). In some embodiments of the method ofdetermining a valid intrinsic frequency of an EEG band of a subject,wherein determining the farthest frequency domain epoch (m_(I)) from themean M comprises calculating an index (I) of the frequency domain epochthat is farthest from the mean (M), wherein I=Index(max_(i)|m_(i)−M|).

In some embodiments, up to eight EEG recordings are performed in anattempt to obtain a valid intrinsic alpha frequency (vIAF) if a validIntrinsic Alpha Frequency is not obtained as previously defined. In someembodiments, the quantitative analysis ends if a valid Intrinsic AlphaFrequency cannot be determined after eight recordings.

Digital Processing Device

In some embodiments, the platforms, systems, media, and methodsdescribed herein include a digital processing device, or use of thesame. In further embodiments, the digital processing device includes oneor more hardware central processing units (CPU) that carry out thedevice's functions. In still further embodiments, the digital processingdevice further comprises an operating system configured to performexecutable instructions. In some embodiments, the digital processingdevice is optionally connected a computer network. In furtherembodiments, the digital processing device is optionally connected tothe Internet such that it accesses the World Wide Web. In still furtherembodiments, the digital processing device is optionally connected to acloud computing infrastructure. In other embodiments, the digitalprocessing device is optionally connected to an intranet. In otherembodiments, the digital processing device is optionally connected to adata storage device.

In accordance with the description herein, suitable digital processingdevices include, by way of non-limiting examples, server computers,desktop computers, laptop computers, notebook computers, sub-notebookcomputers, netbook computers, netpad computers, set-top computers, mediastreaming devices, handheld computers, Internet appliances, mobilesmartphones, tablet computers, personal digital assistants, video gameconsoles, vehicles, and wearable computing devices. Those of skill inthe art will recognize that many smartphones are suitable for use in thesystem described herein. Those of skill in the art will also recognizethat select televisions, video players, and digital music players withoptional computer network connectivity are suitable for use in thesystem described herein. Suitable tablet computers include those withbooklet, slate, and convertible configurations, known to those of skillin the art. Those of skill in the art will recognize wearable computingdevices suitable to work with the platforms, systems, media, and methodsdescribed herein comprise a smart watch, smart glasses (e.g., GoogleGlass®, Microsoft HoloLens®), clothing comprising computing devices, andany other computing device that can be attached to or worn by a personand/or animal.

In some embodiments, the digital processing device includes an operatingsystem configured to perform executable instructions. The operatingsystem is, for example, software, including programs and data, whichmanages the device's hardware and provides services for execution ofapplications. Those of skill in the art will recognize that suitableserver operating systems include, by way of non-limiting examples,FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle®Solaris®, Windows Server®, and Novell® NetWare®. Those of skill in theart will recognize that suitable personal computer operating systemsinclude, by way of non-limiting examples, Microsoft® Windows®, Apple®Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. Insome embodiments, the operating system is provided by cloud computing.Those of skill in the art will also recognize that suitable mobile smartphone operating systems include, by way of non-limiting examples, Nokia®Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google®Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS,Linux®, and Palm® WebOS®. Those of skill in the art will also recognizethat suitable media streaming device operating systems include, by wayof non-limiting examples, Apple TV®, Roku®, Boxee®, Google TV®, GoogleChromecast®, Amazon Fire®, and Samsung® HomeSync®. Those of skill in theart will also recognize that suitable video game console operatingsystems include, by way of non-limiting examples, Sony® PS3®, Sony®PS4®, Microsoft® Xbox 360®, Microsoft Xbox One, Nintendo® Wii®,Nintendo® Wii U®, and Ouya®.

In some embodiments, the device includes a storage and/or memory device.The storage and/or memory device is one or more physical apparatusesused to store data or programs on a temporary or permanent basis. Insome embodiments, the device is volatile memory and requires power tomaintain stored information. In some embodiments, the device isnon-volatile memory and retains stored information when the digitalprocessing device is not powered. In further embodiments, thenon-volatile memory comprises flash memory. In some embodiments, thenon-volatile memory comprises dynamic random-access memory (DRAM). Insome embodiments, the non-volatile memory comprises ferroelectric randomaccess memory (FRAM). In some embodiments, the non-volatile memorycomprises phase-change random access memory (PRAM). In otherembodiments, the device is a storage device including, by way ofnon-limiting examples, CD-ROMs, DVDs, flash memory devices, magneticdisk drives, magnetic tapes drives, optical disk drives, and cloudcomputing based storage. In further embodiments, the storage and/ormemory device is a combination of devices such as those disclosedherein.

In some embodiments, the digital processing device includes a display tosend visual information to a user. In some embodiments, the display is acathode ray tube (CRT). In some embodiments, the display is a liquidcrystal display (LCD). In further embodiments, the display is a thinfilm transistor liquid crystal display (TFT-LCD). In some embodiments,the display is an organic light emitting diode (OLED) display. Invarious further embodiments, on OLED display is a passive-matrix OLED(PMOLED) or active-matrix OLED (AMOLED) display. In some embodiments,the display is a plasma display. In other embodiments, the display is avideo projector. In still further embodiments, the display is acombination of devices such as those disclosed herein.

In some embodiments, the digital processing device includes an inputdevice to receive information from a user. In some embodiments, theinput device is a keyboard. In some embodiments, the input device is apointing device including, by way of non-limiting examples, a mouse,trackball, track pad, joystick, game controller, or stylus. In someembodiments, the input device is a touch screen or a multi-touch screen.In other embodiments, the input device is a microphone to capture voiceor other sound input. In other embodiments, the input device is a videocamera or other sensor to capture motion or visual input. In variousembodiments, the input device is a device capable of recognizing one ormore physical gestures and/or motions. In further embodiments, the inputdevice is a Microsoft Kinect®, Leap Motion®, or the like. In stillfurther embodiments, the input device is a combination of devices suchas those disclosed herein.

Server Configuration

In some embodiments, a suitable server configuration includes about 1,about 2, about 3, about 4, about 5, about 6, about 7, about 8, about 9,about 10, about 20, about 30, about 40, about 50, about 60, about 70,about 80, about 90, about 100, about 200, about 500, about 1000, morethan about 1000 servers, one or more server farms, and cloud-basedserver resource allocation systems. In some embodiments, the servers areco-located. In some embodiments, the servers are located in differentgeographical locations. In some embodiments the servers are housed inthe same rack. In some embodiments, the servers are housed in multipleracks. In some embodiments, the multiple racks are in the samegeographic region. In some embodiments the racks are in differentgeographic regions. In some embodiments, the server is or a plurality ofservers employ a software framework such as Hadoop, Google MapReduce,HBase, and/or Hive, for storage and large-scale processing of data-setson clusters of hardware.

Non-transitory Computer Readable Storage Medium

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include one or more non-transitory computer readablestorage media encoded with a program including instructions executableby the operating system of an optionally networked digital processingdevice. In further embodiments, a computer readable storage medium is atangible component of a digital processing device. In still furtherembodiments, a computer readable storage medium is optionally removablefrom a digital processing device. In some embodiments, a computerreadable storage medium includes, by way of non-limiting examples,CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic diskdrives, magnetic tape drives, optical disk drives, cloud computingsystems and services, and the like. In some cases, the program andinstructions are permanently, substantially permanently,semi-permanently, or non-transitorily encoded on the media.

Computer Program

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include at least one computer program, or use of thesame. A computer program includes a sequence of instructions, executablein the digital processing device's CPU, written to perform a specifiedtask. Computer readable instructions may be implemented as programmodules, such as functions, objects, Application Programming Interfaces(APIs), data structures, and the like, that perform particular tasks orimplement particular abstract data types. In light of the disclosureprovided herein, those of skill in the art will recognize that acomputer program may be written in various versions of variouslanguages.

The functionality of the computer readable instructions may be combinedor distributed as desired in various environments. In some embodiments,a computer program comprises one sequence of instructions. In someembodiments, a computer program comprises a plurality of sequences ofinstructions. In some embodiments, a computer program is provided fromone location. In other embodiments, a computer program is provided froma plurality of locations. In various embodiments, a computer programincludes one or more software modules. In various embodiments, acomputer program includes, in part or in whole, one or more webapplications, one or more mobile applications, one or more standaloneapplications, one or more web browser plug-ins, extensions, add-ins, oradd-ons, or combinations thereof.

Web Application

In some embodiments, a computer program includes a web application. Inlight of the disclosure provided herein, those of skill in the art willrecognize that a web application, in various embodiments, utilizes oneor more software frameworks and one or more database systems. In someembodiments, a web application is created upon a software framework suchas Microsoft® .NET or Ruby on Rails (RoR). In some embodiments, a webapplication utilizes one or more database systems including, by way ofnon-limiting examples, relational, non-relational, object oriented,associative, and XML database systems. In further embodiments, suitablerelational database systems include, by way of non-limiting examples,Microsoft® SQL Server, mySQL™, and Oracle®. Those of skill in the artwill also recognize that a web application, in various embodiments, iswritten in one or more versions of one or more languages. A webapplication may be written in one or more markup languages, presentationdefinition languages, client-side scripting languages, server-sidecoding languages, database query languages, or combinations thereof. Insome embodiments, a web application is written to some extent in amarkup language such as Hypertext Markup Language (HTML), ExtensibleHypertext Markup Language (XHTML), or eXtensible Markup Language (XML).In some embodiments, a web application is written to some extent in apresentation definition language such as Cascading Style Sheets (CSS).In some embodiments, a web application is written to some extent in aclient-side scripting language such as Asynchronous Javascript and XML(AJAX), Flash® Actionscript, Javascript, or Silverlight®. In someembodiments, a web application is written to some extent in aserver-side coding language such as Active Server Pages (ASP),ColdFusion®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor(PHP), Python™, Ruby, Tcl, Smalltalk, WebDNA®, or Groovy. In someembodiments, a web application is written to some extent in a databasequery language such as Structured Query Language (SQL). In someembodiments, a web application integrates enterprise server productssuch as IBM® Lotus Domino®. In some embodiments, a web applicationincludes a media player element. In various further embodiments, a mediaplayer element utilizes one or more of many suitable multimediatechnologies including, by way of non-limiting examples, Adobe® Flash®,HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity®.

Mobile Application

In some embodiments, a computer program includes a mobile applicationprovided to a mobile digital processing device. In some embodiments, themobile application is provided to a mobile digital processing device atthe time it is manufactured. In other embodiments, the mobileapplication is provided to a mobile digital processing device via thecomputer network described herein.

In view of the disclosure provided herein, a mobile application iscreated by techniques known to those of skill in the art using hardware,languages, and development environments known to the art. Those of skillin the art will recognize that mobile applications are written inseveral languages. Suitable programming languages include, by way ofnon-limiting examples, C, C++, C#, Objective-C, Java™, Javascript,Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML withor without CSS, or combinations thereof.

Suitable mobile application development environments are available fromseveral sources. Commercially available development environmentsinclude, by way of non-limiting examples, AirplaySDK, alcheMo,Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework,Rhomobile, and WorkLight Mobile Platform. Other development environmentsare available without cost including, by way of non-limiting examples,Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile devicemanufacturers distribute software developer kits including, by way ofnon-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK,BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, andWindows® Mobile SDK.

Those of skill in the art will recognize that several commercial forumsare available for distribution of mobile applications including, by wayof non-limiting examples, Apple® App Store, Android™ Market, BlackBerry®App World, App Store for Palm devices, App Catalog for webOS, Windows®Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, andNintendo® DSi Shop.

Standalone Application

In some embodiments, a computer program includes a standaloneapplication, which is a program that is run as an independent computerprocess, not an add-on to an existing process, e.g., not a plug-in.Those of skill in the art will recognize that standalone applicationsare often compiled. A compiler is a computer program(s) that transformssource code written in a programming language into binary object codesuch as assembly language or machine code. Suitable compiled programminglanguages include, by way of non-limiting examples, C, C++, Objective-C,COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic, and VB .NET,or combinations thereof. Compilation is often performed, at least inpart, to create an executable program. In some embodiments, a computerprogram includes one or more executable complied applications.

Web Browser Plug-in

In some embodiments, the computer program includes a web browserplug-in. In computing, a plug-in is one or more software components thatadd specific functionality to a larger software application. Makers ofsoftware applications support plug-ins to enable third-party developersto create abilities which extend an application, to support easilyadding new features, and to reduce the size of an application. Whensupported, plug-ins enable customizing the functionality of a softwareapplication. As a non-limiting example, plug-ins are commonly used inweb browsers to play video, generate interactivity, scan for viruses,and display particular file types. Those of skill in the art will befamiliar with several web browser plug-ins including, Adobe® Flash®Player, Microsoft® Silverlight®, and Apple® QuickTime®. In someembodiments, the toolbar comprises one or more web browser extensions,add-ins, or add-ons. In some embodiments, the toolbar comprises one ormore explorer bars, tool bands, or desk bands.

In view of the disclosure provided herein, those of skill in the artwill recognize that several plug-in frameworks are available that enabledevelopment of plug-ins in various programming languages, including, byway of non-limiting examples, C++, Delphi, Java™, PHP, Python™, and VB.NET, or combinations thereof.

Web browsers (also called Internet browsers) are software applications,designed for use with network-connected digital processing devices, forretrieving, presenting, and traversing information resources on theWorld Wide Web. Suitable web browsers include, by way of non-limitingexamples, Microsoft® Internet Explorer®, Mozilla® Firefox®, Google®Chrome, Apple® Safari®, Opera Software® Opera®, and KDE Konqueror. Insome embodiments, the web browser is a mobile web browser. Mobile webbrowsers (also called mircrobrowsers, mini-browsers, and wirelessbrowsers) are designed for use on mobile digital processing devicesincluding, by way of non-limiting examples, handheld computers, tabletcomputers, netbook computers, subnotebook computers, smartphones, musicplayers, personal digital assistants (PDAs), and handheld video gamesystems. Suitable mobile web browsers include, by way of non-limitingexamples, Google® Android® browser, RIM BlackBerry® Browser, Apple®Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® formobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web,Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSP™ browser.

Software Modules

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include software, server, and/or database modules, oruse of the same. In view of the disclosure provided herein, softwaremodules are created by techniques known to those of skill in the artusing machines, software, and languages known to the art. The softwaremodules disclosed herein are implemented in a multitude of ways. Invarious embodiments, a software module comprises a file, a section ofcode, a programming object, a programming structure, or combinationsthereof. In further various embodiments, a software module comprises aplurality of files, a plurality of sections of code, a plurality ofprogramming objects, a plurality of programming structures, orcombinations thereof. In various embodiments, the one or more softwaremodules comprise, by way of non-limiting examples, a web application, amobile application, and a standalone application. In some embodiments,software modules are in one computer program or application. In otherembodiments, software modules are in more than one computer program orapplication. In some embodiments, software modules are hosted on onemachine. In other embodiments, software modules are hosted on more thanone machine. In further embodiments, software modules are hosted oncloud computing platforms. In some embodiments, software modules arehosted on one or more machines in one location. In other embodiments,software modules are hosted on one or more machines in more than onelocation.

Databases

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include one or more databases, or use of the same. Inview of the disclosure provided herein, those of skill in the art willrecognize that many databases are suitable for storage and retrieval ofitem, buyer, and seller information. In various embodiments, suitabledatabases include, by way of non-limiting examples, relationaldatabases, non-relational databases, object oriented databases, objectdatabases, entity-relationship model databases, associative databases,and XML databases. In some embodiments, a database is internet-based. Infurther embodiments, a database is web-based. In still furtherembodiments, a database is cloud computing-based. In other embodiments,a database is based on one or more local computer storage devices.

Input and Output Devices

In some embodiments, the platforms, systems, media, and methodsdisclosed herein include one or more input devices or output devices, oruse of the same. In view of the disclosure provided herein, those ofskill in the art will recognize that many devices are suitable forinputting and/or outputting information EEG data and/or frequencyinformation of a subject. In various embodiments, suitable devicesincludes: a digital display, a keyboard, a touch-screen, computerreadable medium, a EEG sensor, a EEG recording device, an auxiliaryconnection, a USB connection, an electrode, an interactive interface, auser interface, a mouse, a microphone, a joy stick, light pen, ascanner, a graphic tablet, a magnetic ink card reader(micr), opticalcharacter reader(ocr), a computer readable medium reader, optical markreader(omr), or the like.

Validation of the Discrimination Algorithm—Example 2

30 subjects (14 male, 16 female, 33.8±11.5 yrs old) participated in thevalidation study (See ClinicalTrials.gov registration #NCT01370733). Thesubjects had a varied ethnic mix (16 white, 5 Asian, 4 Hispanic, 1Pacific Islander, and 4 mixed races). 15 of the subjects underwent EEGrecording in the morning, and 15 in the afternoon. Each subjectunderwent three different phases: Phase 1: eyes closed, relaxed; Phase2: eyes open; and Phase 3: eyes closed, with muscle artifact.

Three disposable patch Ag—AgCl snap-type electrodes are affixed to thesubject's head, one in the center of the forehead (FpZ) approximately 1″(two fingers) above the nasal bridge between the eyebrows; one on thesubject's forehead right of center (Fp1); and one (OZ) approximately 1″(two fingers) above the protuberance of the occipital bone (inion). EEGrecording is done automatically at the push of the START button on theNeoSync NEST Device. Preferred embodiments of the NeoSync NEST Deviceare described in the related U.S. patent application Ser. Nos.12/237,319, 12/237,328, and 12/237,304, 12/850,547, 12/944,591,13/681,964, all of the above identified applications previouslymentioned are incorporated herein by reference.

In this validation study, the test device is not used to deliver therapyto subject but instead to acquire and interpret EEG signal. The hardwareand/or software module specific to acquiring and interpreting an EEGsignal is internal to the NeoSync NEST Device and is the componentevaluated during this study.

IAF stands for Individual Alpha Frequency; sTMS stands for synchronizedTranscranial Magnetic Stimulation; NVC, MJA, DJB, SC are initials oftechnicians performing the EEG recording; CVS is the initial for anoutside consultant who performed an independent analysis of the EEGrecordings.

There were 4 technicians who recorded EEGs. Two of the technicians (NVCand MJA) were experienced, having performed numerous EEG recordingsduring the NND-3001 NEST clinical trial. The other two technicians (DJBand SC) were inexperienced, having never recorded an EEG with the NESTdevice or otherwise. All four technicians underwent training onelectrode application, device connectivity and use, and EEG acquisitionas part of the study.

To determine the effect of technician experience, we evaluated theaverage number of recordings to obtain a valid EEG during Phase 1. Theexperienced technicians recorded EEGs for 14 subjects, with an averageof 2.57±2.44 recordings for a valid IAF. The inexperienced techniciansrecorded EEGs for 16 subjects, with an average of 2.31±2.47 recordings.Using a 2-tailed t-test, the p value of the number of recording toobtain a valid IAF equals 0.77 and thus, there is no statisticalsignificance between the experienced and inexperienced technicians.Therefore, experience level of the technician is not considered a factorin obtaining a valid IAF.

Among all of the 30 test subjects, average number of EEG recordingattempts to obtain a valid IAF during Phase 1 was 1.57, and number ofsubjects excluded, due to 8 invalid IAF recordings during Phase was 4out of 30, which is 13%. IAF consistency between Phase 1 and Phase 2,Phase 1 and Phase 3 was tested. 0.0% of the test subject had more than1.0 Hz difference.

IAF estimation was also compared to blinded independent calculation ofIAF. The average difference identified across all subjects was 0.175 Hz.Only 1 of the subject, 3.33% of the total number of subjects, had morethan 1.0 Hz difference when compared to blinded independent calculationof IAF.

Average difference between IAF from first recording segment Phase 1 andthe final valid IAF was 0.141 Hz. Only 1 subject, 3.33% of the totalnumber of subjects, had more than 1.0 Hz difference between the IAFmeasured from the first recording segment and the final valid IAF.

The average absolute difference in IAFs between Phase 1 and Phase 2 or 3was 0.33 Hz, which indicates that the measurement is consistent and notgreatly affected by noise artifact. There were no subjects that had adifference in IAFs between phases that is greater than 1.0 Hz. Therewere 5 subjects with absolute difference in IAFs of greater than 0.5 Hzbetween Phase 1 and Phase 2/3. The EEGs of these individuals weregenerally very noisy or had certain characteristics, such as adouble-hump, which led to the difference. The highest absolutedifference was 0.865 Hz. Noise artifact, obtained from jaw clenching,eye rolling behind closed lids, frowning, etc. did not appear to be afactor in obtaining a valid IAF. Based on these results, thediscrimination routine has been shown to be very effective at finding aconsistent, stable, valid IAF and rejecting noisy EEGs.

Interestingly, 14/30 subjects obtained a valid IAF during Phase 2 (eyesopen). Although this is not the preferred method of recording an EEG, itis encouraging that even if subjects are not fully compliant during EEGrecording, a valid IAF may still be found.

One of the technicians, MJA, recorded a disproportionally large numberof noisy EEGs where a valid IAF was unable to be obtained. In order tobetter understand this relationship, a follow-up meeting was scheduledwhere the technician repeated the recording procedure (skin prep,electrode placement, etc.) on an additional subject. Issues identifiedin the recording technique were that an alcohol wipe was not used beforeapplying the abrasive gel, and the rear electrode was placedapproximately 1″ too low, situated almost directly over the inion bone.Neither of these resulted in any excessive noise artifact in an analysisof the EEG recording.

The EEG data from Phase 1 was analyzed independently by CVS, who isexperienced in EEG analysis and algorithm development. His estimatesdiffered on average −0.076 Hz from the IAF produced by the EEGdiscrimination algorithm. The average absolute difference was 0.175 Hz.This independent analysis confirms that the EEG system generatesrepeatable, reliable IAF estimates that correlate well with independentqualitative analysis.

There were specific subjects in the study who had EEGs that were verynoisy or had unique characteristics (e.g., double-hump, out-of-bandpeaks), which gave the algorithm problems in finding a valid IAF.

FIG. 5 shows non-limiting exemplary waveforms from EEGs recorded in oneof the test subject the study is shown. One image is shown per phase.The images were selected as a “typical” 8-second epoch from the entirerecording. The top waveform in each image of a phase is the raw EEG. Thebottom waveform in each image of a phase is a 1028 point (128 Hz samplerate) FFT for the raw EEG waveform, showing the frequency of thedominant peak. Some of the subjects have two images shown for one phase,in order to exemplify variations in alpha activity throughout therecording (not shown).

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. It is intended thatthe following claims define the scope of the invention and that methodsand structures within the scope of these claims and their equivalents becovered thereby.

What is claimed is:
 1. A method of determining a final intrinsic alpha frequency (fIAF) of a subject in a neuro-electroencephalogram (EEG) synchronization therapy comprising: applying an EEG discrimination routine executed by one or more processors and comprising: a) receiving a first EEG recording obtained from an EEG sensor in a time domain; b) segmenting the first EEG recording into a plurality of epochs, each of the plurality of epochs comprising a segment of data, wherein a total number of epochs is N; c) filtering the segment of data of each epoch using a high-pass filter; d) converting each epoch into a frequency domain epoch (i); e) filtering each frequency domain epoch (i) using a smoothing filter; f) calculating an epoch intrinsic alpha frequency (m_(i)) of each frequency domain epoch (i); g) calculating a mean (M) intrinsic alpha frequency (IAF) of all intrinsic alpha frequencies (m_(i-N)), wherein ${M = {\frac{1}{N}{\sum\limits_{i = 1}^{N}m_{i}}}};$ h) determining a farthest frequency domain epoch (m_(i)) from the M, if |m_(I)−M|>0.5 hertz(Hz), removing the farthest frequency domain epoch (m_(I)), decrementing N, and returning to step g), or if |m_(I)−M|≤0.5 Hz, continuing to next step; i) setting fIAF equal to M; and j) outputting the fIAF to a therapy device that delivers a low amplitude stimulation; and delivering, with the therapy device, low amplitude stimulation at the fIAF.
 2. The method of claim 1, wherein a length of the first EEG recording is 128 seconds.
 3. The method of claim 1, wherein the first EEG recording comprises a single-channel recording.
 4. The method of claim 1, wherein the first EEG recording comprises a multi-channel recording, wherein an IAF estimate is made for each channel in an epoch and averaged together, or wherein each channel is treated separately, generating an IAF estimate for each channel for the full EEG recording, and wherein valid IAF estimates from each channel, as determined by step h), are averaged together to generate an fIAF.
 5. The method of claim 4, wherein a channel intrinsic alpha frequency is determined for each channel in the frequency domain epoch (i), and are averaged to generate the epoch intrinsic alpha frequency (m_(i)).
 6. The method of claim 1, wherein a channel of the first EEG recording initially comprises 16 epochs.
 7. The method of claim 1, wherein the epoch intrinsic alpha frequency (m_(i),) of each frequency domain epoch (i) is calculated from 7.0 Hz to 14.0 Hz.
 8. The method of claim 1, wherein the fIAF is from 8.0 Hz to 13.0 Hz.
 9. The method of claim 1, wherein the first EEG recording comprises a sample rate of 128 samples/sec.
 10. The method of claim 1, wherein the epoch intrinsic alpha frequency of each epoch (m_(i)) is determined using a Fast Fourier Transform (FFT).
 11. The method of claim 1, wherein if a standard deviation (SD) of the N epoch IAF values ≥0.75 Hz, a second EEG recording is obtained and the method of claim 1 is repeated using the second EEG recording in place of the first EEG recording.
 12. The method of claim 11, wherein if a second standard deviation (SD) of the N epoch IAF values ≥0.75 Hz, a third EEG recording is obtained and the method of claim 1 is repeated using the third EEG recording in place of the first EEG recording.
 13. The method of claim 12, wherein if a third standard deviation (SD) of the N epoch IAF values ≥0.75 Hz, a range of fIAFs of the first EEG recording, the second EEG recording, and the third EEG recording is calculated, wherein if the range is <2.0 Hz, then the mean value of the fIAFs of the first EEG recording, the second EEG recording, and the third EEG recording is determined to be a valid intrinsic alpha frequency (vIAF).
 14. The method of claim 1, wherein if the fIAF is <8.0 Hz or >13.0 Hz, a second EEG recording is obtained and the method of claim 1 is repeated using the second EEG recording in place of the first EEG recording.
 15. The method of claim 14, wherein if the fIAF calculated using the second EEG recording is <8.0 Hz or >13.0 Hz, a third EEG recording is obtained and the method of claim 1 is repeated using the third EEG recording in place of the first EEG recording.
 16. The method of claim 15, wherein if the fIAF calculated using the third EEG recording is <8.0 Hz or >13.0 Hz, a range of fIAFs of the first EEG recording, the second EEG recording, and the third EEG recording is calculated, wherein if the range is <2.0 Hz, then the mean value of the fIAFs of the first EEG recording, the second EEG recording, and the third EEG recording is determined to be a valid intrinsic alpha frequency (vIAF).
 17. The method of claim 1, wherein if the fIAF of the EEG is from 8.0 Hz to 13.0 Hz and a standard deviation (SD) of the N epoch IAF values is <0.75 Hz, the fIAF is determined to be a valid intrinsic alpha frequency (vIAF).
 18. The method of claim 1, wherein if a standard deviation (SD) of the N epoch IAF values ≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) is <8.0 Hz or >13.0 Hz, then a second EEG recording is obtained and the method of claim 1 is repeated using the second EEG recording in place of the first EEG recording.
 19. The method of claim 18, wherein if a standard deviation (SD) of the N epoch IAF values calculated using the second EEG reading ≥0.75 Hz, or if the final intrinsic alpha frequency (fIAF) calculated using the second EEG reading is <8.0 Hz or >13.0 Hz, then a third EEG recording is obtained and the method of claim 1 is repeated using the third EEG recording in place of the first EEG recording.
 20. The method of claim 19, wherein if the fIAF calculated using the third EEG recording is <8.0 Hz or >13.0 Hz or if the standard deviation (SD) of the N epoch IAF values calculated using the third EEG reading ≥0.75 Hz, a range of fIAFs of the first EEG recording, the second EEG recording, and the third EEG recording is calculated, wherein if the range is <2.0 Hz, then the mean value of the fIAFs the first EEG recording, the second EEG recording, and the third EEG recording is determined to be a valid intrinsic alpha frequency (vIAF). 